Methods, apparatus, systems, and articles of manufacture are disclosed that determine a penetration and a churn of a streaming service. Example apparatus disclosed herein includes processor circuitry to instantiate at least interval determination circuitry to determine an interval between the first tuning event and the second tuning event, the first and second tuning events corresponding to streaming of media in a first household using the streaming service via a media device, characterization circuitry to characterize a status of the first household as subscribed when the interval satisfies a threshold, aggregation circuitry to aggregate statuses of households over a time period, the households including the first household, and penetration determination circuitry to generate first analytical data based on a number of subscribed statuses per a total number of households at a timestamp, the timestamp within the time period.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
G06Q 30/02 - Marketing; Price estimation or determination; Fundraising
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
2.
Predictive Measurement of End-User Activities at Specified Times
Methods and systems for determining if end-users are expected to be receiving transmissions from a multimedia network at a particular time. Data including end-user type, a multimedia network, a particular time slot of the repeating cycles, and a network reach descriptor may be received. End-users may be identified by end-user type. For each end-user, a probability of receiving transmissions from the multimedia network during time slots prior to the particular time slot may be determined, based on previous viewing activities. Each probability may be adjusted by an offset such that an average of the adjusted probabilities corresponds to the network reach descriptor. A determination may be made of whether or not each end-user is expected to have been receiving transmissions from the multimedia network at the particular time slot, based on the adjusted respective probability.
H04N 21/262 - Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission or generating play-lists
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
Methods, apparatus, and systems are disclosed to measure media consumption. An apparatus includes a memory, machine readable instructions, and processor circuitry to instantiate or execute the machine readable instructions to access a domain pattern signature representative of a request to obtain media, the domain pattern signature includes (a) a set of domain names and (b) one or more of a location of the request, a time of the request, or a characteristic of a device used to execute the request, compare the domain pattern signature to one or more reference signatures, determine a first reference signature includes (a) a matching set of domain names and (b) one or more of a matching location of the request, a matching time of the request, or a matching characteristic of the device used to execute the request, and credit the domain pattern signature with an Internet site associated with the first reference signature.
In one aspect, an example method includes a processor (1) applying a feature map network to an image to create a feature map comprising a grid of vectors characterizing at least one feature in the image and (2) applying a probability map network to the feature map to create a probability map assigning a probability to the at least one feature in the image, where the assigned probability corresponds to a likelihood that the at least one feature is an overlay. The method further includes the processor determining that the probability exceeds a threshold, and responsive to the processor determining that the probability exceeds the threshold, performing a processing action associated with the at least one feature.
G06V 10/26 - Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
Example methods and apparatus for associating media devices with a demographic composition of a geographic area are disclosed. Disclosed example apparatus are to obtain a plurality of Internet Protocol addresses assigned to a media device associated with a panel member. Disclosed example apparatus are also to determine a most used Internet Protocol address from the plurality of Internet Protocol addresses, determine a geographic location corresponding to the most used Internet Protocol address, associate a geographic area with the media device in response to a determination that the geographic location corresponds to a location of an internet service provider, determine a demographic profile associated with the geographic area, and associate the demographic profile with the media device.
Methods, apparatus, systems, and articles of manufacture to perform speed-enhanced playback of recorded media are disclosed. Example apparatus to playback media disclosed herein comprise at least one memory, machine-readable instructions, and processor circuitry to execute the machine-readable instructions to parse an audio frame included in the media to determine a number of skip bytes included in the audio frame, compare the number of skip bytes to a threshold, associate the audio frame with a plurality of candidate frames identified in the media when the number of skip bytes satisfies the threshold, and calculate a speed-enhanced playback rate for the media based on the plurality of candidate frames identified in the media.
Methods and systems for determining projected amounts of viewing time of a TV program by end-users are disclosed. Data including end-user type, a TV program descriptor, TV network, and start time of transmission may be received. End-users may be identified by end-user type. A machine-learning model applied to the data and viewing history data may generate parameters for determining how much of the TV program they are each expected to view during a sequence of time intervals. For each end-user, the parameters may be applied to make a determination of temporal-fraction values of the TV program the end-user is expected to view during the time interval, and for each time interval, conditioning values used to condition the determination for the next time interval. Projected subtotals of viewing time may be determined, based on the temporal-fraction values. A projected total amount viewing time of the TV program may then be determined.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
Methods, apparatus, systems and articles of manufacture to monitor media are disclosed. An example apparatus includes memory; computer readable instructions; and processor circuitry to execute the computer readable instructions to: generate a plurality of errors by comparing (a) a plurality of watermarks adjusted by offsets and (b) reference data, the adjusted watermarks corresponding to watermark data with inaccurate timing information for media; identify an offset of the offsets based on the plurality of errors; and adjust timing information of a watermark of the watermarks using the offset to increase an accuracy of the timing information.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
A computing system determines accuracy of sport-related information extracted from a time sequence of digital video frames that represent a sport event, the extracted sport-related information including an attribute that changes over the time sequence. The computing system (a) detects, based on the extracted sport-related information, a pattern of change of the attribute over the time sequence and (b) makes a determination of whether the detected pattern is an expected pattern of change associated with the sport event. If the determination is that the detected pattern is the expected pattern, then, responsive to making the determination, the computing system takes a first action that corresponds to the sport-related information being accurate. Whereas, if the determination is that the detected pattern is not the expected pattern, then, responsive to making the determination, the computing system takes a second action that corresponds to the sport-related information being inaccurate.
Methods, apparatus, systems, and articles of manufacture are disclosed to determine total audience ratings. An example apparatus includes metrics generator circuitry to generate a first audience size for media accessed by first devices of a first media platform at a first level of aggregation, the first level of aggregation corresponding to the media accessed on a first television network and on a first website, generate a second audience size for the media accessed by the first devices of the first media platform at a second level of aggregation, the second level of aggregation corresponding to the media accessed on the first television network and accessed on the first website and a second website, comparator circuitry to compare the first audience size to the second audience size, adjustor circuitry to reduce the first audience size based on the second audience size, and audience determination circuitry to determine a total audience size.
Example methods, apparatus, systems, and articles of manufacture are disclosed for network-based monitoring and serving of media to in-vehicle occupants. An example method includes linking panelist data corresponding to media exposure to first telemetry data collected by a vehicle to create linked panelist-telemetry data; and training a neural network to estimate vehicle occupant demographics based on second telemetry data using a first subgroup of the linked panelist-telemetry data.
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
G06N 3/04 - Architecture, e.g. interconnection topology
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
12.
Methods and Apparatus to Reduce Noise from Harmonic Noise Sources
Methods, apparatus, systems and articles of manufacture are disclosed to reduce noise from harmonic noise sources. An example apparatus includes at least one memory; at least one processor to execute the computer readable instructions to at least: determine a first amplitude value of a frequency component in a frequency spectrum of an audio sample; determine a set of points in the frequency spectrum having at least one of (a) amplitude values within an amplitude threshold of the first amplitude value, (b) frequency values within a frequency threshold of the first amplitude value, or (c) phase values within a phase threshold of the first amplitude value; increment a counter when a distance between (1) a second amplitude value in the set of points and (2) the first amplitude value satisfies a distance threshold; and when the counter satisfies a counter threshold, generate a contour trace based on the set of points.
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
G10L 21/0264 - Noise filtering characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques
13.
METHODS AND APPARATUS TO DETECT MULTIPLE WEARABLE METER DEVICES
Methods, apparatus, systems, and articles of manufacture are disclosed. An example apparatus includes interface circuitry to: obtain primary data from a first meter and a second meter, the primary data including at least one of: (a) acceleration data and (b) short-range wireless communication data; and obtain secondary data from the first meter and the second meter, the secondary data including at least one of: (a) location data and (b) audio data; comparator circuitry to: determine one or more primary factors based on the primary data, the primary factors to include at least one of a correlation coefficient or a difference in connected device sequences; determine one or more secondary factors based on the secondary data; and model executor circuitry to determine, based on the one or more primary factors and the one or more secondary factors, whether the first meter and the second meter correspond to duplicate wear.
A machine may form all or part of a network-based system configured to provide media service to one or more user devices. The machine may be configured to define a station library within a larger collection of media files. In particular, the machine may access metadata that describes a seed that forms the basis on which the station library is to be defined. The machine may determine a genre composition for the station library based on the metadata. The machine may generate a list of media files from the metadata based on a relevance of each media file to the station library. The machine may determine the relevance of each media file based on a similarity of the media file to the genre composition of the station library as well as a comparison of metadata describing the media file to the accessed metadata that describes the seed.
In one aspect, an example method includes (i) extracting a sequence of audio features from a portion of a sequence of media content; (ii) extracting a sequence of video features from the portion of the sequence of media content; (iii) providing the sequence of audio features and the sequence of video features as an input to a transition detector neural network that is configured to classify whether or not a given input includes a transition between different content segments; (iv) obtaining from the transition detector neural network classification data corresponding to the input; (v) determining that the classification data is indicative of a transition between different content segments; and (vi) based on determining that the classification data is indicative of a transition between different content segments, outputting transition data indicating that the portion of the sequence of media content includes a transition between different content segments.
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06N 3/049 - Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 20/40 - Scenes; Scene-specific elements in video content
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating MPEG-4 scene graphs
Example methods, apparatus, systems and articles of manufacture are disclosed to facilitate meter to meter matching for media identification. Example apparatus disclosed herein include an unknown signature comparer, a stack counter, and a reference database updater. The unknown signature comparer is to select a candidate unknown signature segment meeting a threshold length from a set of unknown signature segments collected at a first audience measurement location, and compare individual signatures of the candidate unknown signature segment with a collection of unknown signature segments collected at a second audience measurement location. The stack counter is to count a number of times that the candidate unknown signature segment matches unknown signature segments in the collection, and identify the candidate unknown signature segment as a matched signature segment when the number of times meets a counter threshold. The reference database updater is to store the matched signature segment in a signature reference database.
METHODS AND APPARATUS TO PERFORM COMPUTER-BASED MONITORING OF AUDIENCES OF NETWORK-BASED MEDIA BY USING INFORMATION THEORY TO ESTIMATE INTERMEDIATE LEVEL UNIONS
Methods, apparatus, systems, and articles of manufacture to perform computer-based monitoring of audiences of network-based media using information theory to estimate intermediate level unions are disclosed. An example apparatus to determine a deduplicated, census-based audience metric of media includes panel union calculator circuitry to calculate a threshold statistic corresponding to an intermediate union of a panel hierarchy, and census union calculator circuitry to calculate a deduplicated audience value corresponding to the intermediate union of the census hierarchy based on the threshold statistic.
Systems and methods for monitoring of icon in an external display device are disclosed. Images of an icon displayed in a display device may be continually captured as video frames by a video camera of an icon monitoring system. While operating in a first mode, video frames may be continually analyzed to determine if the captured image matches an active template icon known to match the captured image of the icon. While the captured image matches the active template icon, operating in the first mode continues. Upon detecting a failed match to the active template icon, the system starts operating in a second to search among known template icons for a new match. Upon finding a new match, the active template icon may be updated to the new match, and operation switches back to the first mode. Times of transitions between the first and second modes may be recorded.
G06N 3/082 - Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values for each element of the collection of elements. The method further comprises specifying, in a sketch-frequency table, a set of discrete statistical values associated with the hash values and, for each discrete statistical value of the set of discrete statistical values, information indicative of a frequency at which binary representations of the hash values are associated with the discrete statistical value. The cardinality of the collection of elements is estimated based on the sketch-frequency table.
Methods and apparatus to determine media viewing information for hybrid content delivery are disclosed. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to monitor network traffic associated with at least one device during a media session, determine viewing information associated with the media session based on a consumption data message in the network traffic, the consumption data message transmitted by the at least one device, determine a program identifier of primary content received by the at least one device, the program identifier indicative of a program presented as the primary content by the at least one device, associate a panelist identifier with the viewing information and the program identifier of the primary content, and generate a media session report based on the panelist identifier, the viewing information, and the program identifier.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/235 - Processing of additional data, e.g. scrambling of additional data or processing content descriptors
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
21.
Machine Learning Systems and Methods for Predicting End-User Consumption of Future Multimedia Transmissions
Methods and systems for prediction audience ratings are disclosed. A database of television (TV) viewing data may include program records for a multiplicity of existing TV programs. A system may receive a training plurality of program records from the TV viewing data, and for each program record a most similar TV program based on content characteristics may be identified. A synthetic program record may be constructed by merging features of each record and its most similar record. Audience performance metrics may be omitted from synthetic records. An aggregate of the training plurality of program records and the synthetic program records may be used to train a machine-learning (ML) model to predict audience performance metrics of the new or hypothetical TV programs not yet available for viewing and/or not yet transmitted or streamed.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
22.
Use of Steganographically-Encoded Time Information as Basis to Control Implementation of Dynamic Content Modification
A method and system for controlling implementation of dynamic content modification. The disclosure provides for using at least one steganographically-encoded timestamp in a media stream transmitted to a media client as a basis to determine a transmission delay for media-stream transmission to the media client, and for providing the determined transmission delay as a basis to facilitate control over whether to have the media client implement dynamic content modification. In addition, the disclosure provides for receiving respectively from each of various media clients a report indicating transmission delay determined for the media client based on such steganographically-encoded timestamp data, and using the transmission delays for the media clients to establish a dynamic-content-modification footprint that could be used to control whether, where, and to what extent dynamic content modification will be applied.
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to MPEG-4 scene graphs
Accurately detection of logos in media content on media presentation devices is addressed. Logos and products are detected in media content produced in retail deployments using a camera. Logo recognition uses saliency analysis, segmentation techniques, and stroke analysis to segment likely logo regions. Logo recognition may suitably employ feature extraction, signature representation, and logo matching. These three approaches make use of neural network based classification and optical character recognition (OCR). One method for OCR recognizes individual characters then performs string matching. Another OCR method uses segment level character recognition with N-gram matching. Synthetic image generation for training of a neural net classifier and utilizing transfer learning features of neural networks are employed to support fast addition of new logos for recognition.
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
24.
METHODS AND APPARATUS TO IDENTIFY MEDIA PRESENTATIONS BY ANALYZING NETWORK TRAFFIC
Methods, apparatus, systems, and articles of manufacture are disclosed herein to identify media presentation by analyzing network traffic. Example instructions cause a machine to generate a traffic profile to reduce a computational burden of identifying streaming media being presented on a media presentation device, the traffic profile including first network traffic data indicative of the streaming media; obtain the traffic profile and second network traffic data corresponding to the streaming media; and generate, in response to a score for the second network traffic data meeting a threshold of similarity, a network traffic analysis report identifying the streaming media being presented on the media presentation device.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/233 - Processing of audio elementary streams
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating MPEG-4 scene graphs
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/647 - Control signaling between network components and server or clients; Network processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load or bridging bet
25.
USING MESSAGING ASSOCIATED WITH ADAPTIVE BITRATE STREAMING TO PERFORM MEDIA MONITORING FOR MOBILE PLATFORMS
Methods, apparatus, systems, storage media, etc., to perform media monitoring for mobile platforms using messaging associated with adaptive bitrate streaming are disclosed. An example media platform disclosed herein is to detect an outgoing message to be sent by the mobile platform to stream media in accordance with an online streaming protocol, and associate resource identifier information included in the outgoing message with a time value. The disclosed example media platform is also to transmit the outgoing message to a first server to cause the media to be streamed to the mobile platform, and transmit the resource identifier information and the time value to a second server different from the first server to cause a media impression associated with the mobile platform to be monitored.
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
26.
Method and System for Triggering Use of a Video-On-Demand Service by a Media Presentation Device
A computing system detects that a media presentation device such as a television is in a content-selection mode in which a user is likely to select video content to be presented by the media presentation device, at a time when the media presentation device is not using a video-on-demand service. In response, the computing system causes the media presentation device to present a prompt for user approval to have the media presentation device present video content of the video-on-demand service. By presenting this prompt at a time when the media presentation device is in a content-selection mode and is not using the video-on-demand service, the disclosed mechanism can thereby help foster use of the video-on-demand service.
H04N 21/472 - End-user interface for requesting content, additional data or services; End-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
H04N 21/431 - Generation of visual interfaces; Content or additional data rendering
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies
A disclosed example includes accessing computer-generated impression records, the computer-generated impression records based on network communications received at a server of a database proprietor from client devices, the computer-generated impression records indicative of accesses to media at the client devices; accessing self-reported demographic data and behavioral data from a database of the database proprietor, the self-reported demographic data and the behavioral data corresponding to user accounts registered with the database proprietor and associated with the client devices; comparing the self-reported demographic data with a probability distribution of higher-accuracy demographic data; determining different adjustments for corresponding ones of self-reported demographics of the self-reported demographic data based on the comparison; adjusting the corresponding ones of the self-reported demographics based on corresponding ones of the different adjustments to generate adjusted user demographic data; and assigning the adjusted user demographic data to corresponding ones of the computer-generated impression records.
Methods, apparatus, systems, and articles of manufacture are disclosed to adjust demographic information of user accounts to reflect primary users of the user accounts. An example apparatus includes memory, programmable circuitry, and instructions in the memory, the instructions to cause the programmable circuitry to at least access impression data associated with a user account registered with a database proprietor, the user account associated with first demographics at a database of the database proprietor. The example programmable circuitry is also to determine a primary user of the user account based on the impression data and based on second demographics of multiple users of the user account, the multiple users including the primary user. Additionally, the example programmable circuitry is to modify the first demographics associated with the user account based on at least some of the second demographics, the at least some of the second demographics corresponding to the primary user.
Methods, apparatus, systems, and articles of manufacture are disclosed to determine a duration of media presentation based on tuning session duration. Example apparatus a receiver to obtain a first tuning session duration indicative of an amount of time between channel changes of a first media presentation device at a first media presentation location, a presentation session estimator to select a model from storage, the model selected based on a match of the first tuning session duration and a second tuning session duration, the model including a relation between the second tuning session duration and a first presentation session duration of media presented on a second media presentation device at a second media presentation location, and estimate a second presentation session duration of media presented within the first tuning session duration based on the model.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
30.
METHODS AND APPARATUS TO EXTEND A TIMESTAMP RANGE SUPPORTED BY A WATERMARK
Methods, apparatus, systems and articles of manufacture to extend a time range supported by a watermark are disclosed. Example watermark encoding apparatus disclosed herein determine which one of a plurality of timestamp cycles is to be represented by a timestamp of a watermark, the timestamp including a set of timestamp symbols, a first subset of data symbols and a second subset of data symbols. Disclosed example apparatus also modify the first subset of data symbols of the watermark based on a further timestamp symbol not included in the set of timestamp symbols of the timestamp, but not modify the second subset of data symbols based on the further timestamp symbol, the further timestamp symbol to identify the one of the plurality of timestamp cycles to be represented by the timestamp of the watermark. Disclosed example apparatus further embed the watermark in a piece of media.
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
H04N 21/2389 - Multiplex stream processing, e.g. multiplex stream encrypting
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/8352 - Generation of protective data, e.g. certificates involving content or source identification data, e.g. UMID [Unique Material Identifier]
31.
METHODS AND APPARATUS FOR WIRELESS COMMUNICATION WITH AN AUDIENCE MEASUREMENT DEVICE
Methods, apparatus, systems, and articles of manufacture for communication with an audience metering device are disclosed. An example apparatus includes one or more non-transitory computer readable media, instructions in the apparatus, and one or more processors to execute the instructions. The example one or more processors are to segment a message to be transmitted to a configuration device into a first message segment and a second message segment, store the first message segment in a characteristic memory, and transmit a first advertisement to the configuration device when the first message segment is stored in the characteristic memory. Additionally, the example one or more processors are to after the first message segment has been gathered by the configuration device, store the second message segment in the characteristic memory and transmit a second advertisement to the configuration device when the second message segment is stored in the characteristic memory.
Methods and apparatus to measure brand exposure in media streams are disclosed. Example apparatus disclosed herein are to determine a first histogram based on at least one of luminance components or chrominance components of a first frame of video, and determine a second histogram based on at least one of luminance components or chrominance components of a second frame of the video. Disclosed example apparatus are also to detect a transition in the video based on the first histogram and the second histogram, and responsive to the detection of the transition in the video. Disclosed example apparatus are further to process a region of interest within at least one of the first frame or the second frame to detect a logo in the region of interest.
Methods, apparatus, systems and articles of manufacture are disclosed for efficient media indexing. An example method disclosed herein includes means for initiating a list of hash seeds, the list of hash seeds including at least a first hash seed value and a second hash seed value among other hash seed values, means for generating to generate a first bucket distribution based on the first hash seed value and a first hash function and generate a second bucket distribution based on the second hash seed value used in combination with the first hash seed value, means for determining to determine a first entropy value of the first bucket distribution, wherein data associated with the first bucket distribution is stored in a first hash table and determine a second entropy value of the second bucket distribution.
Methods, apparatus, systems, and articles of manufacture to identify an episode number based on fingerprint and matched viewing information are disclosed. An example method includes processing meter data to identify a presented media based on a bumper included in a media, filtering the meter data based on the identification of the media, selecting a candidate episode, the candidate episode not associated with a known episode label, determining whether the candidate episode appears sequentially after a known episode for a threshold number of presentation locations, and labeling the candidate episode as the next sequential episode after the known episode in response to determining that the candidate episode appears sequentially after the known episode for the threshold number of presentation locations.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/435 - Processing of additional data, e.g. decrypting of additional data or reconstructing software from modules extracted from the transport stream
H04N 21/439 - Processing of audio elementary streams
35.
MULTI-MARKET CALIBRATION OF CONVENIENCE PANEL DATA TO REDUCE BEHAVIORAL BIASES
Example methods, apparatus, systems and articles of manufacture to implement calibration of convenience panel data to reduce behavioral bias are disclosed. Disclosed example apparatus include a distribution estimator to determine a first behavioral distribution for first convenience panel data associated with a first market and a measurement period, determine a second behavioral distribution for second convenience panel data associated with a second market and the measurement period, and determine a third behavioral distribution for probabilistic panel data associated with the second market and the measurement period. Disclosed example apparatus also include a distribution calibrator to calibrate the first behavioral distribution determined for the first convenience panel data associated with the first market based on (i) the second behavioral distribution determined for the second convenience panel data associated with the second market and (ii) the third behavioral distribution determined for the probabilistic panel data associated with the second market.
Methods, apparatus, systems, and articles of manufacture to train an artificial intelligence-based model are disclosed. An example apparatus includes memory; computer readable instructions; and processor circuitry to execute the computer readable instructions to: generate a location value for a neuron in an AI-based model; adjust a characteristic a sinusoidal signal based on a misclassification output by the AI-based model; determine that a trajectory of the sinusoidal signal is within a threshold distance of the location value; adjust the location value in response to the trajectory being within the threshold distance; and adjust a weight that corresponds to the neuron based on the adjusted location value.
Methods and apparatus to estimate cardinality of users represented across multiple bloom filter arrays are disclosed. Examples includes processor circuitry to execute and/or instantiate instructions to generate a first composite Bloom filter array based on first and second Bloom filter arrays. The processor circuitry is to generate a final composite Bloom filter array based on the first composite Bloom filter array and a third Bloom filter array. Different ones of the first, second, and third Bloom filter arrays representative of different sets of users who accessed media. The first, second, and third Bloom filter arrays including differential privacy noise. The processor circuitry to estimate a cardinality of a union of the first, second, and third Bloom filter arrays based on the final composite Bloom filter array.
G06F 16/22 - Indexing; Data structures therefor; Storage structures
G06F 15/80 - Architectures of general purpose stored program computers comprising an array of processing units with common control, e.g. single instruction multiple data processors
In one aspect, an example method to be performed by a vehicle-based media system includes (a) receiving audio content; (b) causing one or more speakers to output the received audio content; (c) using a microphone of the vehicle-based media system to capture the output audio content; (d) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; (e) identifying visual content based at least on the identified reference audio content; and (f) outputting, via a user interface of the vehicle-based media system, the identified visual content.
H04H 20/62 - Arrangements specially adapted for specific applications, e.g. for traffic information or for mobile receivers for local area broadcast, e.g. instore broadcast for transportation systems, e.g. in vehicles
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0207 - Discounts or incentives, e.g. coupons or rebates
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
H04N 21/41 - Structure of client; Structure of client peripherals
H04N 21/414 - Specialised client platforms, e.g. receiver in car or embedded in a mobile appliance
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04R 3/12 - Circuits for transducers for distributing signals to two or more loudspeakers
H04W 4/02 - Services making use of location information
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
39.
DISPLAY DEVICE ON/OFF DETECTION METHODS AND APPARATUS
Display device ON/OFF detection methods and apparatus are disclosed. Example display activity detectors disclosed herein are to extract regions from respective ones of captured video frames, the regions corresponding to a depiction of a display of a monitored media device Disclosed example display activity detectors are also to compute a distance metric that is to represent an amount a first one of the regions of a first one of the captured video frames differs from a corresponding second one of the regions of a second one of the captured video frames. Disclosed example display activity detectors are further to compare the distance metric to a threshold to determine whether the monitored media device is ON or OFF.
Methods, apparatus, systems and articles of manufacture to measure engagement of media consumers based on acoustic environment are disclosed. Example apparatus disclosed herein are to identify media device audio data and ambient environment audio data from sensed audio data collected from an environment, and determine classification data for the media device audio data and the ambient environment audio data. Disclosed example apparatus are also to process the classification data with a machine learning model to calculate an engagement metric. Disclosed example apparatus are further to determine whether at least one individual is engaged with media in the environment based on the engagement metric.
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
G10L 15/06 - Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
In an example implementation, a method is described. The implementation accesses first and second media clips. The implementation also matches a first fingerprint of the first media clip with a second fingerprint of the second media clip and determines an overlap of the first media clip with the second media clip. The implementation also, based on the overlap, merges the first and second media clips into a group of overlapping media clips, transmits, to a client device, data identifying the group of overlapping media clips and specifying a synchronization of the first media clip with the second media clip, and generates for display on a display device of the client computing device, a graphical user interface that identifies the group of overlapping media clips, specifies the synchronization of the first media clip with the second media clip, and allows access to, and manipulation of, the first and second media clips.
G11B 27/28 - Indexing; Addressing; Timing or synchronising; Measuring tape travel by using information detectable on the record carrier by using information signals recorded by the same method as the main recording
Example systems and methods of selection of video frames using a machine learning (ML) predictor program are disclosed. The ML predictor program may generate predicted cropping boundaries for any given input image. Training raw images associated with respective sets of training master images indicative of cropping characteristics for the training raw image may be input to the ML predictor, and the ML predictor program trained to predict cropping boundaries for raw image based on expected cropping boundaries associated training master images. At runtime, the trained ML predictor program may be applied to a sequence of video image frames to determine for each respective video image frame a respective score corresponding to a highest statistical confidence associated with one or more subsets of cropping boundaries predicted for the respective video image frame. Information indicative of the respective video image frame having the highest score may be stored or recorded.
Methods and apparatus to group advertisements by advertisement campaign are disclosed. An example apparatus includes memory; instructions in the apparatus; and processor circuitry to execute the instructions to determine pixel color values from a reference advertisement of an advertisement campaign; remove bits from the pixel color values associated with the reference advertisement; determine a first color proportion corresponding the reference advertisement based on the pixel color values; associate the first color proportion with the advertisement campaign; and identify a second advertisement as associated with the advertisement campaign based on a second color proportion of the second advertisement relative to the first color proportion, the second advertisement different than the reference advertisement.
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/74 - Image or video pattern matching; Proximity measures in feature spaces
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
G06V 20/40 - Scenes; Scene-specific elements in video content
44.
Vehicle-Based Media System with Audio Ad and Navigation-Related Action Synchronization Feature
In one aspect, an example method to be performed by a vehicle-based media system includes (a) receiving audio content; (b) causing one or more speakers to output the received audio content; (c) using a microphone of the vehicle-based media system to capture the output audio content; (d) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; (e) identifying a geographic location associated with the identified reference audio content; and (f) based at least on the identified geographic location associated with the identified reference audio content, outputting, via the user interface of the vehicle-based media system, a prompt to navigate to the identified geographic location.
H04H 20/62 - Arrangements specially adapted for specific applications, e.g. for traffic information or for mobile receivers for local area broadcast, e.g. instore broadcast for transportation systems, e.g. in vehicles
G01C 21/36 - Input/output arrangements for on-board computers
G06Q 30/0207 - Discounts or incentives, e.g. coupons or rebates
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
H04N 21/41 - Structure of client; Structure of client peripherals
H04N 21/414 - Specialised client platforms, e.g. receiver in car or embedded in a mobile appliance
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04R 3/12 - Circuits for transducers for distributing signals to two or more loudspeakers
H04W 4/02 - Services making use of location information
H04W 4/44 - Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]
45.
SIGNATURE MATCHING WITH METER DATA AGGREGATION FOR MEDIA IDENTIFICATION
Example apparatus disclosed herein to implement signature matching with meter data aggregation for use in media identification applications include a match job aggregator to aggregate batches of meter data from a meter to form aggregated meter data associated with the meter, and a hash matcher to identify a valid hash key match between meter hash keys generated from meter signatures in the aggregated meter data and reference hash keys corresponding to a collection of media assets. Disclosed example apparatus also include a signature matcher to align, based on the valid hash key match, a sequence of reference signatures corresponding to a first media asset associated with the valid hash key match and a corresponding sequence of the meter signatures, and compare the sequence of reference signatures and the corresponding sequence of meter signatures to identify media represented by at least a portion of the sequence of the meter signatures.
Systems and methods are provided for filtering at least one media content catalog based on criteria for a station library to generate a first list of candidate tracks for the station library, combining a similarity score and a popularity score for each track of the first list of candidate tracks to generate a total score for each track of the first list of candidate tracks, generating a list of top ranked tracks for the first genre, and returning the list of top ranked tracks of the first genre as part of the station library.
A machine may be configured to generate one or more audio fingerprints of one or more segments of audio data. The machine may access audio data to be fingerprinted and divide the audio data into segments. For any given segment, the machine may generate a spectral representation from the segment; generate a vector from the spectral representation; generate an ordered set of permutations of the vector; generate an ordered set of numbers from the permutations of the vector; and generate a fingerprint of the segment of the audio data, which may be considered a sub-fingerprint of the audio data. In addition, the machine or a separate device may be configured to determine a likelihood that candidate audio data matches reference audio data.
Example methods and systems for inserting information into playing content are described. In some example embodiments, the methods and systems may identify a break in content playing via a playback device, select an information segment representative of information received by the playback device to present during the identified break, and insert the information segment into the content playing via the playback device upon an occurrence of the identified break.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A machine is configured to identify a media file that, when played to a user, is likely to modify an emotional or physical state of the user to or towards a target emotional or physical state. The machine accesses play counts that quantify playbacks of media files for the user. The playbacks may be locally performed or detected by the machine from ambient sound. The machine accesses arousal scores of the media files and determines a distribution of the play counts over the arousal scores. The machine uses one or more relative maxima in the distribution in selecting a target arousal score for the user based on contextual data that describes an activity of the user. The machine selects one or more media files based on the target arousal score. The machine may then cause the selected media file to be played to the user.
Methods, apparatus, and systems are disclosed for estimating audience exposure based on engagement level. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to identify a user activity associated with a user during exposure of the user to media based on an output from at least one of a user device, a remote control device, an image sensor, or a motion sensor, classify the user activity as an attention-based activity or a distraction-based activity, assign a distraction factor or an attention factor to the user activity based on the classification, and determine an attention level for the user based on the distraction factor or the attention factor.
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
51.
METHODS, SYSTEMS, ARTICLES OF MANUFACTURE, AND APPARATUS TO ESTIMATE AUDIENCE POPULATION
Methods, apparatus, systems, and articles of manufacture are disclosed to estimate an audience population. An example apparatus includes processor circuitry; characteristic identifier instructions to be executed by the processor circuitry to determine whether respective ones of respondents are associated with a characteristic; recapture probability estimator instructions to be executed by the processor circuitry to select a recapture probability of the respective ones of respondents; and population estimator instructions to be executed by the processor circuitry to in response to the recapture probability satisfying a recapture threshold, determine a population estimate having the characteristics based on a first model; and in response to the recapture probability not satisfying the recapture threshold, determine the population estimate having the characteristics based on a second model, the second model different than the first model.
H04H 60/33 - Arrangements for monitoring the users' behaviour or opinions
H04H 60/45 - Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users for identifying users
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
52.
MODIFICATION OF ELECTRONIC SYSTEM OPERATION BASED ON ACOUSTIC AMBIENCE CLASSIFICATION
Methods and systems for modification of electronic system operation based on acoustic ambience classification are presented. In an example method, at least one audio signal present in a physical environment of a user is detected. The at least one audio signal is analyzed to extract at least one audio feature from the audio signal. The audio signal is classified based on the audio feature to produce at least one classification of the audio signal. Operation of an electronic system interacting with the user in the physical environment is modified based on the classification of the audio signal.
In one aspect, an example method to be performed by a computing device includes (a) determining that a ride-sharing session is active; (b) in response to determining the ride-sharing session is active, using a microphone of the computing device to capture audio content; (c) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; (d) determining that the ride-sharing session is inactive; and (e) outputting an indication of the identified reference audio content.
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
G06F 16/68 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
54.
Synchronizing Streaming Media Content Across Devices
Methods, apparatus, and systems are disclosed for synchronizing streaming media content. An example apparatus includes a storage device, and a processor to execute instructions to identify a first source streaming broadcast media to a first computing device based on an audio fingerprint of audio associated with the broadcast media, identify sources broadcasting the broadcast media streaming to the first computing device, the sources available to a second computing device including the processor, select a second source of the identified sources for streaming the broadcast media to the second computing device, the second source different than the first source, detect termination of the streaming of the broadcast media on the first computing device, the termination corresponding to a termination time of the broadcast media, and automatically start, by using the selected second source, streaming of the broadcast media to the second computing device at the termination time.
H04N 21/43 - Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronizing decoder's clock; Client middleware
H04N 21/439 - Processing of audio elementary streams
H04H 60/40 - Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users for identifying broadcast time or space for identifying broadcast time
H04H 60/58 - Arrangements characterised by components specially adapted for monitoring, identification or recognition covered by groups or of audio
H04H 60/65 - Arrangements for services using the result of monitoring, identification or recognition covered by groups or for using the result on users' side
H04L 65/611 - Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio for multicast or broadcast
55.
OBTAINING ARTIST IMAGERY FROM VIDEO CONTENT USING FACIAL RECOGNITION
An example method may include receiving, at a computing device, a digital image associated with a particular media content program, the digital image containing one or more faces of particular people associated with the particular media content program. A computer-implemented automated face recognition program may be applied to the digital image to recognize, based on at least one feature vector from a prior-determined set of feature vectors, one or more of the particular people in the digital image, together with respective geometric coordinates for each of the one or more detected faces. At least a subset of the prior-determined set of feature vectors may be associated with a respective one of the particular people. The digital image together may be stored in non-transitory computer-readable memory, together with information assigning respective identities of the recognized particular people, and associating with each respective assigned identity geometric coordinates in the digital image.
G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
56.
METHODS AND APPARATUS TO ASSIGN VIEWERS TO MEDIA METER DATA
Methods, apparatus, systems and articles of manufacture to assign viewers to media meter data are disclosed. An apparatus includes processor circuitry to execute computer readable instructions to at least: identify a candidate household from a plurality of second households to associate with a first household based on an analysis of a first duration of time first media was presented by a first media presentation device and a second duration of time second media was presented by second media presentation devices; match different ones of first panelists of the first household with matching ones of second panelists of the candidate household; and impute respective portions of the first duration of time to the different ones of the first panelists based on portions of the second duration of time for which the matching ones of the second panelists of the candidate household were exposed to the second media.
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
57.
Methods and Apparatus for Harmonic Source Enhancement
Methods and apparatus for harmonic source enhancement are disclosed herein. An example apparatus includes an interface to receive a media signal. The example apparatus also includes a harmonic source enhancer to determine a magnitude spectrogram of audio corresponding to the media signal; generate a time-frequency mask based on the magnitude spectrogram; and apply the time-frequency mask to the magnitude spectrogram to enhance a harmonic source of the media signal.
G10K 11/175 - Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
G10L 25/18 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
58.
METHODS AND APPARATUS TO EXPAND PANELIST ENROLLMENT
Methods, apparatus, systems and articles of manufacture to expand panelist enrollment are disclosed. An example first media device includes processor circuitry to at least one of instantiate or execute the machine readable instructions to scan at least one local area network to which the first media device is connected, store an identification of a second media device connected to the at least one local area network, in response to scan of the at least one local area network indicating that the second media device is commonly connected to the at least one local area network with the first media device, add the identification of the second media device to a fingerprint, and transmit the fingerprint to a central facility.
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
Methods, apparatus, systems and articles of manufacture are disclosed for playback using pre-processed profile information and personalization. Example apparatus disclosed herein include a synchronizer to, in response to receiving a media signal to be played on a playback device, access an equalization (EQ) profile corresponding to the media signal; an EQ personalization manager to generate a personalized EQ setting; and an EQ adjustment implementor to modify playback of the media signal on the playback device based on a blended equalization generation based on the EQ profile and the personalized EQ setting.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
G06N 3/04 - Architecture, e.g. interconnection topology
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
H04N 9/87 - Regeneration of colour television signals
H04N 21/439 - Processing of audio elementary streams
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies
60.
GENERATION OF MEDIA STATION PREVIEWS USING A REFERENCE DATABASE
In one aspect, an example method includes (i) while a media playback device of a vehicle is playing back content received on a first channel, sending, by the media playback device to a server, a preview request, the preview request identifying a second channel that is different from the first channel; (ii) receiving, by the media playback device from the server, a response to the preview request, the response including identifying information corresponding to content being provided on the second channel; and (iii) while the media playback device is playing back the content received on the first channel, providing, by the media playback device for display, at least a portion of the identifying information corresponding to content being provided on the second channel.
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to MPEG-4 scene graphs
H04N 21/472 - End-user interface for requesting content, additional data or services; End-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content
H04N 21/2387 - Stream processing in response to a playback request from an end-user, e.g. for trick-play
H04N 21/278 - Content descriptor database or directory service for end-user access
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies
Methods, apparatus, systems, and articles of manufacture are disclosed to measure audience exposure to media streams with a wireless isochronous data link. In one example, an apparatus includes a datastore, a network interface circuitry, and processor circuitry. The network interface circuitry obtains a first copy of audio data from a first wireless data link, the audio data transmitted from an audio source device, wherein a second copy of the audio data is transmitted, synchronously to the first copy of the audio data, to an audio sink device over a second wireless data link. The processor circuitry to instantiate data parsing circuitry to parse a media stream identifier from the first copy of the audio data and media identification assignment circuitry to assign the media stream identifier to an audio data log for the audio sink device.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/85 - Assembly of content; Generation of multimedia applications
Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate de-duplicated unknown total audience sizes based on partial information of known audiences. An example apparatus includes an association controller to generate a tree structure association corresponding to a union of first and second margins of time; and one or more commercial solvers to: perform parallel computations on a processor to determine multipliers by solving equations corresponding to the tree structure association, the multipliers corresponding to the first total audience size for the union, the second total audience size for the first margin, and the third total audience size for the second margin; and determine an estimate for the third total audience size for the second margin of time based on the multipliers.
Techniques of providing motion video content along with audio content are disclosed. In some example embodiments, a computer-implemented system is configured to perform operations comprising: receiving primary audio content; determining that at least one reference audio content satisfies a predetermined similarity threshold based on a comparison of the primary audio content with the at least one reference audio content; for each one of the at least one reference audio content, identifying motion video content based on the motion video content being stored in association with the one of the at least one reference audio content and not stored in association with the primary audio content; and causing the identified motion video content to be displayed on a device concurrently with a presentation of the primary audio content on the device.
H04N 21/43 - Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronizing decoder's clock; Client middleware
H04N 21/439 - Processing of audio elementary streams
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies
64.
METHODS AND APPARATUS FOR DYNAMIC VOLUME ADJUSTMENT VIA AUDIO CLASSIFICATION
Methods, apparatus, systems and articles of manufacture are disclosed for dynamic volume adjustment via audio classification. Example apparatus include at least one memory; instructions; and at least one processor to execute the instructions to: analyze, with a neural network, a parameter of an audio signal associated with a first volume level to determine a classification group associated with the audio signal; determine an input volume of the audio signal; determine a classification gain value based on the classification group; determine an intermediate gain value as an intermediate between the input volume and the classification gain value by applying a first weight to the input volume and a second weight to the classification gain value; apply the intermediate gain value to the audio signal, the intermediate gain value to modify the first volume level to a second volume level; and apply a compression value to the audio signal, the compression value to modify the second volume level to a third volume level that satisfies a target volume threshold.
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
65.
METHODS AND APPARATUS TO MONITOR STREAMING MEDIA CONTENT
Methods, apparatus, systems and articles of manufacture are disclosed to monitor streaming media content. Example apparatus disclosed herein include means for determining whether a streaming media flag is asserted in a payload of a watermark detected in media presented by a media presentation device, the streaming media flag to indicate whether the media was distributed to the media presentation device as streaming media. Disclosed example apparatus also include means for discarding the detected watermark from collected data in response to a determination that the streaming media flag is asserted. Disclosed example apparatus further include means for reporting the collected data to a remote server via a network.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04L 43/062 - Generation of reports related to network traffic
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
Methods and apparatus to measure exposure to streaming media are disclosed. An example apparatus includes communication interface circuitry to obtain metering data, the metering data including a first metadata tag extracted from media at a time corresponding to a media event associated with the media, the metering data omitting second metadata tags extracted from the media by a media monitor, the second metadata tags identified for omission based on a temporal proximity of the second metadata tags to the media event, the first and second metadata tags extracted from the media when the media is presented; memory; instructions included in the apparatus; and processor circuitry to execute the instructions to determine a first exposure of an audience to the media based on the metering data, the first exposure being the same as a second exposure determined based on an analysis of the first metadata tags.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/437 - Interfacing the upstream path of the transmission network, e.g. for transmitting client requests to a VOD server
H04N 21/6587 - Control parameters, e.g. trick play commands or viewpoint selection
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/658 - Transmission by the client directed to the server
H04N 21/435 - Processing of additional data, e.g. decrypting of additional data or reconstructing software from modules extracted from the transport stream
67.
METHODS AND APPARATUS TO REDIRECT INTERNET CLIENTS FOR MEDIA MONITORING
Methods, apparatus, systems and articles of manufacture are disclosed to redirect internet clients for media monitoring. An example apparatus disclosed herein includes memory, instructions, and processor circuitry to execute the instructions to detect connections between client devices and a first WI-FI connection point, the client devices connected to the first WI-FI connection point via a second WI-FI connection point, when a first number of the connections is less than a second number of possible connections to the first WI-FI connection point, generate an additional connection to the first WI-FI connection point, the additional connection corresponding to at least one of the client devices, and route the client devices to the first WI-FI connection point via the first number of connections and the additional connection.
Methods and apparatus to detect user attentiveness to portable devices are disclosed. An example portable device includes memory, computer readable instructions, and processor circuitry to execute the computer readable instructions to at least download an exposure measurement application from a first server via a network, and execute the exposure measurement application to detect at least one of a first orientation change of the portable device or a first position change between the portable device and a user, compare the at least one of the first orientation change or the first position change to a plurality of spatial condition change combinations associated with respective likelihoods indicative of user attentiveness related to the portable device to determine user attentiveness data associated with a presentation on the portable device, and cause the user attentiveness data to be transmitted via the network.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/32 - Arrangements for monitoring conditions of receiving stations, e.g. malfunction or breakdown of receiving stations
H04N 21/41 - Structure of client; Structure of client peripherals
H04N 21/61 - Network physical structure; Signal processing
Apparatus, systems, articles of manufacture, and methods for volume adjustment are disclosed herein. An example method includes collecting data corresponding to a volume of an audio signal as the audio signal is output through a device, when an average volume of the audio signal does not satisfy a volume threshold for a specified timespan, determining a difference between the average volume and a desired volume, and applying a gain to the audio signal to adjust the volume of the audio signal to the desired volume, the gain determined based on the difference between the average volume and the desired volume.
Example apparatus disclosed herein are to compare first monitored media signatures associated with an advertisement block to a plurality of sequences of monitored media signatures associated with a first time period; determine a start boundary and an end boundary of a first advertisement in the advertisement block based on the comparison of the first monitored media signatures and the plurality of sequences of monitored media signatures, the first advertisement associated with second monitored media signatures representative of a subset of the first monitored media signatures between the start boundary and the end boundary; generate an entry in an advertisement relationship graph for the second monitored media signatures, the entry to map second monitored media signatures to the first advertisement; and credit media exposure to the first advertisement based on the second monitored media signatures in the advertisement relationship graph.
H04N 21/2668 - Creating a channel for a dedicated end-user group, e.g. by inserting targeted commercials into a video stream based on end-user profiles
Example apparatus disclosed herein are to send a request to a media provider that is to cause the media provider to initiate transmission of a transport stream that is to provide streaming media to a media presentation device. Disclosed example apparatus are also to extract metering metadata from a data file to be received by the media presentation device after the transmission of the transport stream is initiated by the media provider but before receipt by the media presentation device of the transport stream that is to provide the streaming media to the media presentation device, the data file associated with the transport stream. Disclosed example apparatus are further to report the metering metadata to a server in response to a detected event, and access an identification of secondary media responsive to the report of the metering metadata, the secondary media to be presented by the media presentation device.
Methods and apparatus to incorporate saturation effects into marketing mix models are disclosed. An example apparatus includes means for converting adstock data associated with an advertising campaign into effective reached realized (ERR) data based on a first saturation curve, the adstock data corresponding to adstocked gross rating points generated from marketing mix input data. The apparatus further including means for performing regression analysis to: identify the first saturation curve from among a plurality of plausible curves based on a fit of different ones of the plurality of plausible curves to the marketing mix input data, the first saturation curve to define a relationship indicative of saturation effects of the advertising campaign on a target audience of the advertising campaign; and determine an impact of the advertising campaign on sales during a period of interest based on a regression analysis of the ERR data relative to sales data.
Example apparatus disclosed herein are to access first data entries from a first data source based on a first media identifier, the first data entries associated with first streaming media, respective ones of the first data entries including the first media identifier and corresponding timestamps that indicate when the first streaming media was presented or accessed via a group of media devices. Disclosed example apparatus are also to access second data entries from a second data source based on a keyword or phrase, the second data entries associated with news information or weather information. Disclosed example apparatus are further to align, based on the timestamps, the second data entries with values of a time varying audience of the first streaming media determined based on the first data entries to determine ratings data that correlates changes in the time varying audience with the news information or the weather information.
Systems and methods for monitoring malicious software engaging in online advertising fraud or other form of deceit are disclosed herein. An example method includes identifying a communication process used by a compromised computing device to communicate with a control server, the control server providing access to advertising weblinks, the compromised computing device associated with malicious software, directing, by an instruction executed by a processor, the compromised computing device to communicate with an uncompromised computing device by re-routing of packets used for communication between the compromised computing device and the control server, the uncompromised computing device is configured to mimic communications between the compromised computing device and the control server using the communication processes, storing information from one or more packets transmitted from the uncompromised computing device, and creating a profile of the malicious software based on the stored information.
G06F 21/53 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by executing in a restricted environment, e.g. sandbox or secure virtual machine
Example methods, apparatus, systems and articles of manufacture to implement an addressable measurement framework are disclosed. Example apparatus disclosed herein perform a common homes analysis of provider data and panel data to determine a coverage footprint associated with the provider data, the provider data including at least one of return path data reported by a plurality of set-top boxes or automatic content recognition data reported by a plurality of smart media devices, and the panel data reported by media device meters. Disclosed example apparatus also weight a portion of the provider data based on the common homes analysis, weight a portion of the panel data based on the common homes analysis, and calculate an addressable advertisement rating based on the weighted portion of the provider data and the weighted portion of the panel data.
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to MPEG-4 scene graphs
H04N 21/4722 - End-user interface for requesting content, additional data or services; End-user interface for interacting with content, e.g. for content reservation or setting reminders, for requesting event notification or for manipulating displayed content for requesting additional data associated with the content
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies
H04N 21/433 - Content storage operation, e.g. storage operation in response to a pause request or caching operations
76.
METHODS AND APPARATUS TO ESTIMATE POPULATION REACH FROM DIFFERENT MARGINAL RATING UNIONS
Example methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach for different unions based on marginal ratings. An example apparatus includes memory and processor circuitry to determine a population reach estimate of a union of time intervals for which media ratings data is available, the population reach estimate based on a pseudo universe estimate of a population audience corresponding to the union of the time intervals; determine a pseudo universe estimate of a recorded audience corresponding to the union of the time intervals; determine the pseudo universe estimate of the population audience based on the pseudo universe estimate of the recorded audience; and in response to a decision to update the pseudo universe estimate of the population audience to reduce an error of the population reach estimate output the population reach estimate of the union when the error of the population reach estimate satisfies a threshold.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
77.
POWER EFFICIENT DETECTION OF WATERMARKS IN MEDIA SIGNALS
Example apparatus disclosed herein include a watermark detector to detect watermarks in a media signal. Disclosed example apparatus also include a controller to operate the watermark detector to (1) detect a first watermark in the media signal, and (2) cycle between sleep intervals and active intervals based on a repetition rate of the watermarks in the media signal to perform a detection operation for a second watermark at a second location in the media signal relative to a first location of the first watermark in the media signal. In some examples, the controller is to search a buffer of prior detected watermark symbols to detect a third watermark at a third location prior to the second location in the media signal in response to the second watermark not being detected at the second location in the media signal.
H04N 21/443 - OS processes, e.g. booting an STB, implementing a Java virtual machine in an STB or power management in an STB
H04N 21/439 - Processing of audio elementary streams
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
H04N 19/467 - Embedding additional information in the video signal during the compression process characterised by the embedded information being invisible, e.g. watermarking
H04N 19/42 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals - characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
78.
METHODS AND APPARATUS TO IDENTIFY ALTERNATE LANGUAGE VERSIONS OF MEDIA BASED ON SIGNATURE MATCHING
Methods and apparatus to identify alternate language versions of media based on signature matching are disclosed. Example apparatus disclosed herein include a signature matcher to compare signatures in monitored data with reference signatures to determine signature match strengths associated with portions of the monitored data, the reference signatures associated with reference media assets. Disclosed example apparatus also include a data segmenter to divide the monitored data into first and second segments, the first segments including temporally adjacent portions of the monitored data having signature match strengths that satisfy a threshold, the second segments including temporally adjacent portions of the monitored data having signature match strengths that do not satisfy the threshold. Disclosed example apparatus further includes a trend determiner to determine, based on a pattern of the first and second segments, whether the monitored data is associated with an alternative language version of one of the reference media assets.
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to MPEG-4 scene graphs
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
79.
METHODS AND APPARATUS TO COLLECT IMPRESSIONS ASSOCIATED WITH OVER-THE-TOP MEDIA DEVICES
Methods, apparatus, and systems are disclosed to collect impressions associated with over-the-top media devices. An example apparatus includes memory; and at least one processor to execute instructions to access a first request, the first request from a user-controlled client device, the first request including an over-the-top device identifier that identifies an over-the-top device that presents media, in response to determining a user of the user-controlled client device is a panelist of a first server, store the over-the-top device identifier with demographics corresponding to the panelist, access a second request, the second request from the over-the-top device, the second request including the over-the-top device identifier and a media identifier, and log an impression associated with the media identifier and the demographics, the impression corresponding to the panelist of the first server.
Methods, apparatus, systems and articles of manufacture are disclosed for identification of streaming activity and source for cached media on streaming devices. An example system stores, in a content identification information library, first content identification information of a first media presentation, wherein the first media presentation is a streamed media presentation; inspects a network connection of a media streaming device for network activity associated with a second media presentation; determine, in response to an absence of the network activity, the second media presentation is a cached media presentation; infers a streaming source of the second media presentation by matching second content identification information of the second media presentation with the first content identification information of the first media presentation; and generates a second media credit for the second media presentation that includes an inferred streaming source identifier.
H04N 21/231 - Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers or prioritizing data for deletion
H04N 21/658 - Transmission by the client directed to the server
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/432 - Content retrieval operation from a local storage medium, e.g. hard-disk
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04L 65/61 - Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio
H04L 67/568 - Storing data temporarily at an intermediate stage, e.g. caching
H04N 21/235 - Processing of additional data, e.g. scrambling of additional data or processing content descriptors
81.
Use of Mismatched Query Fingerprint as Basis to Validate Media Identification
A method for controlling presentation of metadata regarding media. A system could generate query fingerprints representing media content being presented, the media content having been identified as being a first media-content item. The system could further detect a threshold mismatch comprising at least one of the query fingerprints not matching any of first reference fingerprints known to represent the first media-content item. In response, the system could engage in new media identification, establishing that the media content is a second media-content item, and could obtain both second reference fingerprints known to represent the second media-content item and metadata regarding the second media-content item. Further, the system could validate the new identification as a condition precedent to presenting the obtained metadata, the validating including comparing with the obtained second digital reference fingerprints the at least one digital query fingerprint that did not match any of the first digital reference fingerprints.
G06F 16/483 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Methods, apparatus, systems, and articles of manufacture are disclosed to detect a presence status. An example apparatus includes media identification circuitry to generate first signatures representative of first audio data associated with a monitored media device, a comparator to obtain second signatures from a portable meter, the second signatures representative of second audio data sensed by the portable meter and compare the first signatures and the second signatures to determine a comparison result, presence detection circuitry to determine a presence status of a user based on the comparison result, the user associated with the portable meter, and network communication circuitry to transmit the presence status to a data processor to perform audience measurement based on the presence status.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
H04N 21/439 - Processing of audio elementary streams
H04L 67/54 - Presence management, e.g. monitoring or registration for receipt of user log-on information, or the connection status of the users
Methods and apparatus are disclosed to identify users associated with device application usage. A disclosed example method involves obtaining demographics of persons to participate in a panel for an audience research study, identifying a set of applications to be monitored, providing devices associated with the persons in the panel with a meter to record usage of the applications and with a user-to-application associator, the user-to-application associator to define associations between the applications to be monitored and the persons associate with the device before the applications are launched, receiving data from a first one of the devices identifying a first one of the persons as a primary user of a first one of the applications in the set of applications, receiving data from the first device identifying usage of the first application, and associating the demographics of the first person with the usage of the first application.
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
H04L 67/04 - Protocols specially adapted for terminal portability
H04L 67/125 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
Methods and apparatus to credit streaming activity using domain level bandwidth information are disclosed. An example apparatus includes a packet collector to collect data packets via a network interface, and a traffic analyzer to determine domain data of the data packets and associate bandwidth usage values with the domain data to define bandwidth usage data by domain. The apparatus also includes a bandwidth usage data storage to store the associated bandwidth usage data by domain.
An apparatus and method to automatically determine the location of unknown media devices is disclosed. An example apparatus includes a media device detector to detect an unknown media device identified in monitoring data collected by an audience measurement device at a location determined to have an “on” status, a media transmission detector to detect a media transmission associated with a device address and an association storer to store an association of the device address, the unknown media device and the location. A probability determiner determines a probability that the unknown media device is located at the location.
H04L 12/18 - Arrangements for providing special services to substations for broadcast or conference
H04L 43/0876 - Network utilisation, e.g. volume of load or congestion level
H04L 51/043 - Real-time or near real-time messaging, e.g. instant messaging [IM] using or handling presence information
H04L 51/222 - Monitoring or handling of messages using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
86.
METHODS AND APPARATUS TO COLLECT DISTRIBUTED USER INFORMATION FOR MEDIA IMPRESSIONS
A disclosed example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to store a logged media impression for a media identifier representative of media accessed via the Internet, cause transmission of a device identifier or a user identifier to a database proprietor when a user has not elected to not participate in third-party tracking corresponding to online activities, access user information from the database proprietor based on the device identifier or the user identifier, log a demographic impression based on the media impression and the user information, and generate an impression report corresponding to the media based on the demographic impression.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
H04N 21/61 - Network physical structure; Signal processing
G06Q 30/0201 - Market modelling; Market analysis; Collecting market data
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
Methods, apparatus, systems and articles of manufacture are disclosed to generate a signature based on signature candidates. An example apparatus disclosed herein includes first means for determining an alignment point of a first candidate signature segment and a second candidate signature segment, the first candidate signature segment and the second candidate signature segment include time data and signature data, the alignment point based on the time data of the first candidate signature segment and the time data of the second candidate signature segment, means for comparing a first signature to a second signature at the alignment point, the first signature representative of media included in the first candidate signature segment, the second signature included in the second candidate signature segment, and means for stitching the second signature to the first signature based on the comparison to generate a stitched signature, the stitched signature to be used for media crediting.
H04N 21/8352 - Generation of protective data, e.g. certificates involving content or source identification data, e.g. UMID [Unique Material Identifier]
Methods and apparatus to estimate census-level audience sizes and duration data across dimensions and/or demographics are disclosed. An example apparatus includes constraint equation control circuitry to select at least one constraint equation corresponding to one or more events, the one or more events corresponding to first audience members and second audience members, the first audience members to include the second audience members, constraint parameter estimation circuitry to solve the at least one constraint equation to determine one or more constraint parameter values, the one or more constraint parameter values corresponding to the one or more events, and output generation circuitry to determine, based on one or more intermediate equations and the one or more constraint parameter values, an event audience size and an event duration corresponding to (a) the first audience members and (b) a combination of the one or more events and one or more demographics.
Methods, apparatus, systems and articles of manufacture are disclosed to monitor wireless traffic. An example apparatus disclosed herein includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to: establish, via a first wireless interface, a wireless connection with first network credentials to match second network credentials of a primary access point; monitor traffic via a second wireless interface, the second wireless interface different than the first wireless interface; identify, via the traffic monitored via the second wireless interface, a connection of a client to the primary access point; capture, via an alternate access point, a management frame transmitted from the primary access point to the client; insert a change channel announcement into the captured management frame; and re-transmit, via the first wireless interface, the captured management frame including the change channel announcement.
Methods, apparatus, systems and articles of manufacture are disclosed for identification of local commercial insertion opportunities. Example apparatus for identification of local commercial insertion opportunities include a media comparator to compare respective instances of media conveyed in respective ones of a plurality of broadcast signals associated with affiliates of a national broadcaster to identify a broadcast interval having different media conveyed among at least some of the broadcast signals. The example apparatus also include an insertion opportunity identifier to determine whether the broadcast interval is associated with a local advertisement insertion opportunity based on a characteristic of the broadcast interval.
Methods, apparatus, systems and articles of manufacture are disclosed. An example apparatus includes an audio detector to determine a first audience count based on signatures of audio data captured in the media environment, a thermal image detector to determine a heat blob count based on a frame of thermal image data captured in the media environment, and an audience image detector to identify at least one audience member based on a comparison of a frame of audience image data with a library of reference audience images, the audience image detector to perform the comparison in response to the first audience count not matching the heat blob count.
G06V 40/10 - Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
G10L 25/78 - Detection of presence or absence of voice signals
G06V 10/75 - Image or video pattern matching; Proximity measures in feature spaces using context analysis; Selection of dictionaries
92.
METHODS AND APPARATUS TO DETERMINE PROBABILISTIC MEDIA VIEWING METRICS
Methods and apparatus to determine probabilistic media viewing metrics are disclosed herein. An example apparatus includes memory including machine reachable instructions; and processor circuitry to execute the instructions to calculate a first probability for respective ones of a plurality of panelists as having viewed media based on viewing data, the viewing data including incomplete viewing data for one or more of the panelists relative to the media; identify respective ones of a plurality of panelists as included in a demographic subgroup based on demographic data for the panelists; assign a sampling weight to the respective ones of the plurality of panelists based on the demographic data; and calculate a second probability of the demographic subgroup having viewed the media based on the first probabilities and the sampling weights for the respective ones of the plurality of panelists in the demographic subgroup.
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
93.
METHODS AND APPARATUS TO IDENTIFY MEDIA USING HYBRID HASH KEYS
Apparatus, system, methods, and articles of manufacture are disclosed to identify media using hash keys. An example system includes a hybrid hash key analyzer to access a metered hash key of an exposure record obtained from a meter, access reference records representative of respective portions of a plurality of media, and determine reference confirmation data candidates from respective ones of the reference records that include hash keys matching the metered hash key. The example system includes an impression logger to, when first confirmation data associated with the exposure record matches one of the reference confirmation data candidates, store an impression record that associates the media identification data associated with the matching one of the reference confirmation data candidates with a meter identifier of the exposure record. The impression logger also is to credit at least a portion of the media corresponding to the media identification data with an exposure credit.
Methods and apparatus to generate reference signatures are disclosed. An example method includes collecting a first signature for media being presented to a plurality of households; crediting the media when the first signature matches a reference signature in a reference signature database; in response to determining that the first signature does not match a reference signature in the reference signature database and the first signature does not match an unidentified signature in an unknown signature database, storing the first signature in the unknown signature database; in response to determining that a second signature does not match the reference signature in the reference signature database and the second signature matches the unidentified signature in the unknown signature database, and increasing a count associated with the unidentified signature
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/56 - Arrangements characterised by components specially adapted for monitoring, identification or recognition covered by groups or
H04H 60/31 - Arrangements for monitoring the use made of the broadcast services
95.
METHODS AND SYSTEMS TO MONITOR A MEDIA DEVICE VIA A USB PORT
An audience measurement computing system for monitoring a media presentation device in a monitored environment is described and includes a network interface, at least one processor, and a non-transitory computer-readable medium comprising instructions executable by the processor(s). The computing system is configured to obtain, via a cable connected to an input port of the media presentation device, a voltage signal generated by the media presentation device based on an operational state of the media presentation device; compare voltage indicated by the voltage signal to a threshold; based on the comparing, generate timestamped operational state data comprising a record indicative of when the media presentation device is in an on-state; obtain audience measurement data representing one or more media signals communicated to the media presentation device; and transmit, via the network interface over a network and to a central facility, the timestamped operational state data and the audience measurement data.
G06Q 30/0242 - Determining effectiveness of advertisements
G01R 19/165 - Indicating that current or voltage is either above or below a predetermined value or within or outside a predetermined range of values
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
Methods, apparatus, systems, and articles of manufacture for reconciliation of commercial measurement ratings for non-return path data media devices are disclosed. Example apparatus disclosed herein are to estimate unreported addressable impressions for a plurality of unreported households for an addressable advertisement based on an impressions adjustment ratio of served reportable addressable impressions to exposed reported addressable impressions included in impressions data associated with reported households. Disclosed example apparatus are further to calculate at least one of reach or frequency for the addressable advertisement to account for non-reporting devices, the at least one of the reach or the frequency determined based on the exposed reported addressable impressions, the estimated unreported addressable impressions, and the impressions adjustment ratio.
G06Q 30/0242 - Determining effectiveness of advertisements
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04H 60/64 - Arrangements for services using the result of monitoring, identification or recognition covered by groups or for providing detail information
97.
METHODS AND APPARATUS FOR IDENTIFYING MEDIA CONTENT USING TEMPORAL SIGNAL CHARACTERISTICS
Methods and apparatus for identifying media content using temporal signal characteristics are disclosed. An example apparatus includes at least one memory, computer readable instructions, and at least one processor to execute the instructions to identify intervals in a media signal; generate interval sums for respective ones of the intervals, a first interval sum of the interval sums based on a sum of magnitudes of first peaks of the media signal that occur between zero crossings of a first interval of the intervals of the media signal; identify second peaks based on the interval sums; and generate a signature representative of the media signal based on the second peaks.
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating MPEG-4 scene graphs
H04H 60/58 - Arrangements characterised by components specially adapted for monitoring, identification or recognition covered by groups or of audio
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
H04N 21/439 - Processing of audio elementary streams
98.
METHODS AND APPARATUS TO IMPROVE USAGE CREDITING IN MOBILE DEVICES
Methods, apparatus, systems and articles of manufacture are disclosed including means for identifying to identify a first request having a first source port number, from a device, determine whether a second request, having a second source port number, is within a threshold number of ports from the first source port number, group the first and the second requests as a first session when the second source port number is within the threshold number of ports from the first source port number, and means for classifying to generate session windows, the session windows including the threshold number of ports, wherein the session windows are applied to lowest and highest source port numbers associated with a current session.
Methods, apparatus, systems and articles of manufacture are disclosed for media crediting and, more particularly, methods and apparatus of media device detection for minimally invasive media meters. An example apparatus disclosed herein to detect media devices presenting media includes means for generating a cluster of media locations from a reference population of media locations based on media identifying information received from a presentation of media at an unidentified media device at a first media location, means for determining media devices available at the media locations in the cluster of media locations, means for identifying the unidentified media device based on (1) the media devices available at the media locations in the cluster of media locations and (2) an identity of a media device determined to be available in a majority of media locations in the cluster of media locations.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/54 - Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users for identifying locations where broadcast information is generated
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/2547 - Third party billing, e.g. billing of advertiser
H04N 21/658 - Transmission by the client directed to the server
H04H 60/00 - Arrangements for broadcast applications with a direct linkage to broadcast information or to broadcast space-time; Broadcast-related systems
H04N 21/435 - Processing of additional data, e.g. decrypting of additional data or reconstructing software from modules extracted from the transport stream
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
100.
METHODS AND APPARATUS TO VERIFY PRESENTATION OF MEDIA CONTENT
Example methods and apparatus to verify presentation of media content are disclosed. A disclosed example apparatus for generating media presentation information includes a comparator to periodically output a value indicative of whether media selected via a set-top box is presented at a media presentation location by comparing a first audio signal associated with the media to ambient audio received in the media presentation location via an audio system associated with a media presentation device. The example apparatus also includes a privacy protector to facilitate operation of the comparator by periodically preventing the comparator from receiving of the ambient audio. The example apparatus also includes a metering module to record presentation of the media based on the output.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/31 - Arrangements for monitoring the use made of the broadcast services
H04N 21/436 - Interfacing a local distribution network, e.g. communicating with another STB or inside the home
H04N 7/16 - Analogue secrecy systems; Analogue subscription systems
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04N 21/439 - Processing of audio elementary streams
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
