Abstract: One high-level aspect of a content-modification system and related methods may involve facilitating content modification by a content-presentation device of received broadcast content in a controlled manner, while under circumstances in which some events that can impact timing may be unpredictable. In particular, certain operations by a content-presentation device may involve matching received content with specific expected content as determined by one or another component of the content-modification system, in order to confirm proper conditions are met for the content-presentation device to proceed with, or continue, content-modification operations. It can happen the matching procedure becomes subject or susceptible to timing irregularities, or jitter. In some instances, jitter may impact the ability to derive the benefits of content modification. Accordingly, example embodiments herein are directed to systems and method for compensation and/or mitigating the effects of jitter.

Abstract: One high-level aspect of a content-modification system and related methods may involve facilitating content modification by a content-presentation device of received broadcast content in a controlled manner, while under circumstances in which some events that can impact timing may be unpredictable. In particular, certain operations by a content-presentation device may involve matching received content with specific expected content as determined by one or another component of the content-modification system, in order to confirm proper conditions are met for the content-presentation device to proceed with, or continue, content-modification operations. It can happen the matching procedure becomes subject or susceptible to timing irregularities, or jitter. In some instances, jitter may impact the ability to derive the benefits of content modification. Accordingly, example embodiments herein are directed to systems and method for compensation and/or mitigating the effects of jitter.

Abstract: One high-level aspect of a content-modification system and related methods may involve facilitating content modification by a content-presentation device of received broadcast content in a controlled manner, while under circumstances in which some events that can impact timing may be unpredictable. In particular, certain operations by a content-presentation device may involve matching received content with specific expected content as determined by one or another component of the content-modification system, in order to confirm proper conditions are met for the content-presentation device to proceed with, or continue, content-modification operations. It can happen the matching procedure becomes subject or susceptible to timing irregularities, or jitter. In some instances, jitter may impact the ability to derive the benefits of content modification. Accordingly, example embodiments herein are directed to systems and method for compensation and/or mitigating the effects of jitter.

Abstract: In one aspect, a method includes identifying an upcoming content-modification opportunity on a channel, where the upcoming content-modification opportunity relates to a modifiable content-segment transmitted by a content-distribution system on the channel, and where the modifiable content-segment includes an overlay content portion and a non-overlay content portion. The method also includes responsive to identifying the upcoming content-modification opportunity on the channel, identifying a content-presentation device tuned to the channel. The method also includes determining location data associated with the overlay content portion.

Abstract: Audio distortion compensation methods to improve accuracy and efficiency of audio content identification are described. The method is also applicable to speech recognition. Methods to detect the interference from speakers and sources, and distortion to audio from environment and devices, are discussed. Additional methods to detect distortion to the content after performing search and correlation are illustrated. The causes of actual distortion at each client are measured and registered and learnt to generate rules for determining likely distortion and interference sources. The learnt rules are applied at the client, and likely distortions that are detected are compensated or heavily distorted sections are ignored at audio level or signature and feature level based on compute resources available. Further methods to subtract the likely distortions in the query at both audio level and after processing at signature and feature level are described.

Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

Abstract: In one aspect, an example method includes (i) determining, by a playback device, a loudness level of first media content that the playback device is receiving from a first source; (ii) comparing, by the playback device, the determined loudness level of the first media content with a reference loudness level indicated by a loudness level profile for the first media content; (iii) determining, by the playback device, a target volume level for the playback device based on a difference between the determined loudness level of the first media content and the reference loudness level; and (iv) while the playback device presents second media content from a second source in place of the first media content, adjusting, by the playback device, a volume of the playback device toward the target volume level.

Abstract: A mobile device responds in real time to media content presented on a media device, such as a television. The mobile device captures temporal fragments of audio-video content on its microphone, camera, or both and generates corresponding audio-video query fingerprints. The query fingerprints are transmitted to a search server located remotely or used with a search function on the mobile device for content search and identification. Audio features are extracted and audio signal global onset detection is used for input audio frame alignment. Additional audio feature signatures are generated from local audio frame onsets, audio frame frequency domain entropy, and maximum change in the spectral coefficients. Video frames are analyzed to find a television screen in the frames, and a detected active television quadrilateral is used to generate video fingerprints to be combined with audio fingerprints for more reliable content identification.

Abstract: Audio distortion compensation methods to improve accuracy and efficiency of audio content identification are described. The method is also applicable to speech recognition. Methods to detect the interference from speakers and sources, and distortion to audio from environment and devices are discussed. Additional methods to detect distortion to the content after performing search and correlation are illustrated. The causes of actual distortion at each client are measured and registered and learnt to generate rules for determining likely distortion and interference sources. The learnt rules are applied at the client, and likely distortions that are detected are compensated or heavily distorted sections are ignored at audio level or signature and feature level based on compute resources available. Further methods to subtract the likely distortions in the query at both audio level and after processing at signature and feature level are described.

Abstract: In one aspect, a method includes identifying an upcoming content-modification opportunity on a channel, where the upcoming content-modification opportunity relates to a modifiable content-segment transmitted by a content-distribution system on the channel, and where the modifiable content-segment includes an overlay content portion and a non-overlay content portion. The method also includes responsive to identifying the upcoming content-modification opportunity on the channel, identifying a content-presentation device tuned to the channel. The method also includes determining location data associated with the overlay content portion.

Abstract: A multi-dimensional database and indexes and operations on the multi-dimensional database are described which include video search applications or other similar sequence or structure searches. Traversal indexes utilize highly discriminative information about images and video sequences or about object shapes. Global and local signatures around keypoints are used for compact and robust retrieval and discriminative information content of images or video sequences of interest. For other objects or structures relevant signature of pattern or structure are used for traversal indexes. Traversal indexes are stored in leaf nodes along with distance measures and occurrence of similar images in the database. During a sequence query, correlation scores are calculated for single frame, for frame sequence, and video clips, or for other objects or structures.

Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

Abstract: In one aspect, an example method includes (i) determining, by a playback device, a first loudness level of a first portion of first media content from a first source while the playback device presents the first media content, with the first portion having a first length; (ii) switching, by the playback device, from presenting the first media content from the first source to presenting second media content from a second source; (iii) based on the switching, determining, by the playback device, second loudness levels of second portions of the first media content while the playback device presents the second media content, with the second portions having a second length that is shorter than the first length; and (iv) while the playback device presents the second media content, adjusting, by the playback device, a volume of the playback device based on one or more of the second loudness levels.

Abstract: In one aspect, a method includes (i) accessing, by a computing system, broadcast-schedule data associated with a channel; (ii) using, by the computing system, the accessed broadcast-schedule data to identify an upcoming content-modification opportunity on the channel; (iii) determining, by the computing system, that a content-presentation device is receiving content on the channel; (iv) determining, by the computing system, a content-transmission delay associated with the content-presentation device and the channel; and (v) causing, by the computing system, the content-presentation device to perform an action to facilitate the content-presentation device performing, during a time-period that accounts for the determined content-transmission delay, a content-modification operation related to the identified upcoming content-modification opportunity on the channel.

Abstract: In one aspect, an example method includes (i) determining, by a playback device, a loudness level of first media content that the playback device is receiving from a first source; (ii) comparing, by the playback device, the determined loudness level of the first media content with a reference loudness level indicated by a loudness level profile for the first media content; (iii) determining, by the playback device, a target volume level for the playback device based on a difference between the determined loudness level of the first media content and the reference loudness level; and (iv) while the playback device presents second media content from a second source in place of the first media content, adjusting, by the playback device, a volume of the playback device toward the target volume level.

Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

Abstract: In one aspect, an example method includes (i) determining, by a playback device, a first loudness level of a first portion of first media content from a first source while the playback device presents the first media content, with the first portion having a first length; (ii) switching, by the playback device, from presenting the first media content from the first source to presenting second media content from a second source; (iii) based on the switching, determining, by the playback device, second loudness levels of second portions of the first media content while the playback device presents the second media content, with the second portions having a second length that is shorter than the first length; and (iv) while the playback device presents the second media content, adjusting, by the playback device, a volume of the playback device based on one or more of the second loudness levels.

Abstract: The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.

Abstract: An architecture for a multimedia search system is described. To perform similarity matching of multimedia query frames against reference content, reference database comprising of a cluster index using cluster keys to perform similarity matching and a multimedia index to perform sequence matching is built. Methods to update and maintain the reference database that enables addition and removal of the multimedia contents, including portions of multimedia content, from the reference database in a running system are described. Hierarchical multi-level partitioning methods to organize the reference database are presented. Smart partitioning of the reference multimedia content according to the nature of the multimedia content, and according to the popularity among the social media, that supports scalable fast multimedia identification is also presented.