Abstract: This document describes techniques and apparatuses enabling brand detection in audiovisual media. The techniques detect a brand exposed within audiovisual media, such as a name or logo for a product or service, and based on this brand, present a brand advertisement or enable selection of an interactive experience that is associated with the brand. By so doing, marketers enable viewers to quickly and easily learn more about the product or service.

Abstract: Systems and methods for identifying and searching video are disclosed. A video search and identification system includes a catalog representing relationships between video, data and/or objects to enable querying and search based on visual representations of video as well as data or other information associated with the video. In one example, the catalog includes video nodes, metadata nodes and card nodes, although additional or fewer node types may be used. A visual-based video identification system is provided to identify content in video sources. An unidentified video source is accessed and visual fingerprints of one or more frames are generated as query signatures for matching against a base set of known signatures. Confidence measures are generated at the bit level to assist in query signature processing.

Abstract: A computer program and apparatus function to extract objects from a video by identifying regions to be tracked, tracking the regions across several frames, calculating motions of the regions, and identifying new regions to be tracked. Regions of a selected frame of the video that are appropriate for tracking are selected. Tracking of the identified regions is then performed across frames subsequent to the selected frame of the video. Motions of the identified regions are calculated, and new regions for tracking are identified.

Abstract: A method of extracting objects from a video includes the identification of regions to be tracked, tracking the regions across several frames, calculating motions of the regions, and identifying new regions to be tracked. Regions of a selected frame of the video that are appropriate for tracking are selected. Tracking of the identified regions is then performed across frames subsequent to the selected frame of the video. Motions of the identified regions are calculated, and new regions for tracking are identified.

Abstract: A method analyzes the visual content of media such as videos for collecting together visually-similar appearances in their constituent images (e.g. same scenes, same objects, faces of the same people.) As a result, the most relevant and salient (of clearest and largest presence) visual appearances depicted in the videos are presented to the user, both for the sake of summarizing the video content for the users to “see before they watch” (that is, judge by the depicted video content in a filmstrip-like summary whether they want to mouse-click on the video and actually spend time watching it), as well as for allowing to users to further refine their video search result set according to the most relevant and salient video content returned (e.g. largest screen-time faces).

Abstract: A method analyzes the visual content of media such as videos for collecting together visually-similar appearances in their constituent images (e.g. same scenes, same objects, faces of the same people.) As a result, the most relevant and salient (of clearest and largest presence) visual appearances depicted in the videos are presented to the user, both for the sake of summarizing the video content for the users to “see before they watch” (that is, judge by the depicted video content in a filmstrip-like summary whether they want to mouse-click on the video and actually spend time watching it), as well as for allowing to users to further refine their video search result set according to the most relevant and salient video content returned (e.g. largest screen-time faces).

Abstract: A method analyzes the visual content of media such as videos for collecting together visually-similar appearances in their constituent images (e.g. same scenes, same objects, faces of the same people.) As a result, the most relevant and salient (of clearest and largest presence) visual appearances depicted in the videos are presented to the user, both for the sake of summarizing the video content for the users to “see before they watch” (that is, judge by the depicted video content in a filmstrip-like summary whether they want to mouse-click on the video and actually spend time watching it), as well as for allowing to users to further refine their video search result set according to the most relevant and salient video content returned (e.g. largest screen-time faces).

Abstract: A video visual and audio query system for quickly identifying video within a large known corpus of videos being played on any screen or display. In one embodiment, the system can record via a mobile phone camera and microphone a live video clip from the TV and transcode it into a sequence of frame-signatures. The signatures representative of the clips can then be matched against the signatures of the TV content in a corpus across a network to identify the correct TV show or movie.

Abstract: A method of processing an image includes the steps of computing a plurality of line averages for a first image; identifying a set of pairs of line averages having high edge strengths; identifying a set of maximal pairs of line averages from among the set of line averages having high edge strength; expanding each of the maximal pairs of line averages into line stacks to form a set of line stacks; applying the set of line stacks to a second image so as to compute lines averages for the second image; shifting the line stacks to center the stacks on areas of highest edge strength and computing a distance between line stacks of the first and second images.

Abstract: An apparatus and software for processing an image reduces the number of pixels constituting the image by sequentially eliminating alternate rows and columns of pixels, the information represented by each pixel being eliminated (a “source” pixel) being redistributed into adjacent “destination” pixel locations. The redistribution is made in proportion to the similarity between the source and each destination pixel, e.g., similarity of color and/or luminance values.

Abstract: A method of processing an image reduces the number of pixels constituting the image by sequentially eliminating alternate rows and columns of pixels, the information represented by each pixel being eliminated (a “source” pixel) being redistributed into adjacent “destination” pixel locations. The redistribution is made in proportion to the similarity between the source and each destination pixel, e.g., similarity of color and/or luminance values.

Abstract: A method analyzes the visual content of media such as videos for collecting together visually-similar appearances in their constituent images (e.g. same scenes, same objects, faces of the same people.) As a result, the most relevant and salient (of clearest and largest presence) visual appearances depicted in the videos are presented to the user, both for the sake of summarizing the video content for the users to “see before they watch” (that is, judge by the depicted video content in a filmstrip-like summary whether they want to mouse-click on the video and actually spend time watching it), as well as for allowing to users to further refine their video search result set according to the most relevant and salient video content returned (e.g. largest screen-time faces).

Abstract: A method analyzes the visual content of media such as videos for collecting together visually-similar appearances in their constituent images (e.g. same scenes, same objects, faces of the same people.) As a result, the most relevant and salient (of clearest and largest presence) visual appearances depicted in the videos are presented to the user, both for the sake of summarizing the video content for the users to “see before they watch” (that is, judge by the depicted video content in a filmstrip-like summary whether they want to mouse-click on the video and actually spend time watching it), as well as for allowing to users to further refine their video search result set according to the most relevant and salient video content returned (e.g. largest screen-time faces).

Abstract: A method of processing an image includes the steps of computing a plurality of line averages for a first image; identifying a set of pairs of line averages having high edge strengths; identifying a set of maximal pairs of line averages from among the set of line averages having high edge strength; expanding each of the maximal pairs of line averages into line stacks to form a set of line stacks; applying the set of line stacks to a second image so as to compute lines averages for the second image; shifting the line stacks to center the stacks on areas of highest edge strength and computing a distance between line stacks of the first and second images.

Abstract: A method of extracting objects from a video includes the identification of regions to be tracked, tracking the regions across several frames, calculating motions of the regions, and identifying new regions to be tracked. Regions of a selected frame of the video that are appropriate for tracking are selected. Tracking of the identified regions is then performed across frames subsequent to the selected frame of the video. Motions of the identified regions are calculated, and new regions for tracking are identified.

Abstract: A method assigns tags to and descriptive of content. Assigned to the tags are respective weights with respect to the content. The tags and associated weights may be stored in a memory. The weights may be indicative of an importance of the tags to respective portions of the content. The content may be any of a wide range of content and/or file types including, but not limited to, video, audio, text and signal files. Highlights corresponding to selected portions of the files may be identified and provided for user review. The stored information may be searched based on search terms associated with tags together with the weights to be associated with each tag, the weights indicative of an importance of items identified by corresponding tags with respect to the identified content.

Abstract: A computer program and apparatus function to extract objects from a video by identifying regions to be tracked, tracking the regions across several frames, calculating motions of the regions, and identifying new regions to be tracked. Regions of a selected frame of the video that are appropriate for tracking are selected. Tracking of the identified regions is then performed across frames subsequent to the selected frame of the video. Motions of the identified regions are calculated, and new regions for tracking are identified.

Abstract: An apparatus assigns tags to and descriptive of content. Assigned to the tags are respective weights with respect to the content. The tags and associated weights may be stored in a memory. The weights may be indicative of an importance of the tags to respective portions of the content. The content may be any of a wide range of content and/or file types including, but not limited to, video, audio, text and signal files. Highlights corresponding to selected portions of the files may be identified and provided for user review. The stored information may be searched based on search terms associated with tags together with the weights to be associated with each tag, the weights indicative of an importance of items identified by corresponding tags with respect to the identified content.

Abstract: A method assigns tags to and descriptive of content. Assigned to the tags are respective weights with respect to the content. The tags and associated weights may be stored in a memory. The weights may be indicative of an importance of the tags to respective portions of the content. The content may be any of a wide range of content and/or file types including, but not limited to, video, audio, text and signal files. Highlights corresponding to selected portions of the files may be identified and provided for user review. The stored information may be searched based on search terms associated with tags together with the weights to be associated with each tag, the weights indicative of an importance of items identified by corresponding tags with respect to the identified content.

Abstract: A method and apparatus for clustering data, particularly regarding an image, that constructs a graph in which each node of the graph represents a pixel of the image, and every two nodes represent neighboring pixels associated by a coupling factor. Block pixels are selected with unselected neighboring pixels coupled with a selected block to form aggregates. The graph is coarsened recursively by performing iterated weighted aggregation to form larger blocks (aggregates) and obtain hierarchical decomposition of the image while forming a pyramid structure over the image. Saliency of segments is detected in the pyramid, and by computing recursively, a degree of attachment of every pixel to each of the blocks in the pyramid. The pyramid is scanned from coarse to fine starting at the level a segment is detected, to lower levels and rebuilding the pyramid before continuing to the next higher level. Relaxation sweeps sharpen the boundaries of a segment.