Abstract:
A system and methodology provide for annotating videos with entities and associated probabilities of existence of the entities within video frames. A computer-implemented method selects an entity from a plurality of entities identifying characteristics of a video item, where the video item has associated metadata. The computer-implemented method receives probabilities of existence of the entity in video frames of the video item, and selects a video frame determined to comprise the entity responsive to determining the video frame having a probability of existence of the entity greater than zero. The computer-implemented method determines a scaling factor for the probability of existence of the entity using the metadata of the video item, and determines an adjusted probability of existence of the entity by using the scaling factor to adjust the probability of existence of the entity. The computer-implemented method labels the video frame with the adjusted probability of existence.
Abstract:
A search result is modified to include a predetermined number of channels within a predetermined number of a plurality of entries in the search result. The search result is generated in response to a search query. The search result is modified to comprise a predetermined number of channels within a predetermined number of the plurality of entries. The modified search result is updated based on the plurality of entries and a subset of the updated modified search result is selected to be presented in response to the search query. The subset of the updated modified search result comprises the channel and at least one selection of data content.
Abstract:
A search result is modified to include a predetermined number of channels within a predetermined number of a plurality of entries in the search result. The search result is generated in response to a search query. The search result is modified to comprise a predetermined number of channels within a predetermined number of the plurality of entries. The modified search result is updated based on the plurality of entries and a subset of the updated modified search result is selected to be presented in response to the search query. The subset of the updated modified search result comprises the channel and at least one selection of data content.
Abstract:
A search result is modified to include a predetermined number of channels within a predetermined number of a plurality of entries in the search result. The search result is generated in response to a search query. The search result is modified to comprise a predetermined number of channels within a predetermined number of the plurality of entries. The modified search result is updated based on the plurality of entries and a subset of the updated modified search result is selected to be presented in response to the search query. The subset of the updated modified search result comprises the channel and at least one selection of data content.
Abstract:
A computer-implemented method for selecting representative frames for videos is provided. The method includes receiving a video and identifying a set of features for each of the frames of the video. The features including frame-based features and semantic features. The semantic features identifying likelihoods of semantic concepts being present as content in the frames of the video. A set of video segments for the video is subsequently generated. Each video segment includes a chronological subset of frames from the video and each frame is associated with at least one of the semantic features. The method generates a score for each frame of the subset of frames for each video segment based at least on the semantic features, and selecting a representative frame for each video segment based on the scores of the frames in the video segment. The representative frame represents and summarizes the video segment.
Abstract:
Systems and methods for identifying duplicate media items in a media system are provided. In particular, media content can be uploaded to a serve. The media content can be fingerprinted. A digest is generated based on the fingerprint. The digest is indexed and potential matching media items are identified. Matches are determined from the potential matching media items.