Data Recognition in Content
First Claim
1. A method, comprising:
- performing, by a computing device, scene segmentation on video content, resulting in data that defines a plurality of scenes in the video content;
identifying a set of entities in the video content;
for a first scene in the plurality of scenes, identifying a plurality of confidence value vectors representative of features of the first scene, wherein at least one vector of the plurality of confidence value vectors includes a confidence value for at least one entity in the set of entities; and
for the first scene, determining a vector of presence identifiers based at least in part on the plurality of confidence value vectors, wherein at least one identifier in the vector of presence identifiers defines whether an entity in the set of entities is present in the first scene.
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Abstract
The disclosure relates to recognizing data such as items or entities in content. In some aspects, content may be received and feature information, such as face recognition data and voice recognition data may be generated. Scene segmentation may also be performed on the content, grouping the various shots of the video content into one or more shot collections, such as scenes. For example, a decision lattice representative of possible scene segmentations may be determined and the most probable path through the decision lattice may be selected as the scene segmentation. Upon generating the feature information and performing the scene segmentation, one or more items or entities that are present in the scene may be identified.
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Citations
20 Claims
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1. A method, comprising:
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performing, by a computing device, scene segmentation on video content, resulting in data that defines a plurality of scenes in the video content; identifying a set of entities in the video content; for a first scene in the plurality of scenes, identifying a plurality of confidence value vectors representative of features of the first scene, wherein at least one vector of the plurality of confidence value vectors includes a confidence value for at least one entity in the set of entities; and for the first scene, determining a vector of presence identifiers based at least in part on the plurality of confidence value vectors, wherein at least one identifier in the vector of presence identifiers defines whether an entity in the set of entities is present in the first scene. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An apparatus, comprising:
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one or more processors; memory storing computer-executable instructions configured to, with the one or more processors, cause the apparatus to; perform scene segmentation on video content, resulting in data that defines a plurality of scenes in the video content; identify a set of entities in the video content; for a first scene in the plurality of scenes, identify a plurality of confidence value vectors representative of features of the first scene, wherein at least one vector of the plurality of confidence value vectors includes a confidence value for at least one entity in the set of entities; and for the first scene, determine a vector of presence identifiers based at least in part on the plurality of confidence value vectors, wherein at least one identifier in the vector of presence identifiers defines whether an entity in the set of entities is present in the first scene. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A method comprising:
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performing feature recognition on video content using a plurality of feature recognition techniques, resulting in feature information for the video content; performing, by a computing device, scene segmentation on the video content, wherein the scene segmentation is based on one or more probabilities that the one or more identified shots in the video content are a scene boundary or a non-scene boundary, and wherein performing the scene segmentation results in data that defines one or more scenes in the video content; identify, from the feature information, a set of confidence value vectors for a first scene of the one or more scenes, wherein a first vector of the set of confidence value vectors is from a first of the plurality of feature recognition techniques, and a second vector of the set of confidence value vectors is from a second of the plurality of feature recognition techniques; and identify one or more items present in the first scene based on the set of confidence value vectors. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification