Abstract: Devices, systems, and methods are provided for enhanced video annotations using image analysis. A method may include identifying, by a first device, first faces of first video frames, and second faces of second video frames. The method may include determining a first score for the first video frames, the first score indicative of a first number of faces to label, the first number of faces represented by the first video frames, and determining a second score for the second video frames, the second score indicative of a second number of faces to label. The method may include selecting the first video frames for face labeling, and receiving a first face label for the first face. The method may include generating a second face label for the second faces. The method may include sending the first face label and the second face label to a second device for presentation.

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for automated identification and tagging of video content. Example methods may include determining a first set of frames in video content, determining a first set of faces that appear in the first set of frames, and extracting first image content corresponding to respective faces of the first set of faces. Methods may include classifying the first image content into a first set of clusters, generating a second set of clusters comprising a second set of faces, wherein the second set of faces has less faces than the first set of faces, and determining a first actor identifier associated with a first face in the second set of clusters. Some methods may include determining second image content in the second set of clusters comprising the first face, and automatically associating the first actor identifier with the second image content.

Abstract: Methods and apparatus are described for automating aspects of the annotation of a media presentation. Events are identified that relate to entities associated with the scenes of the media presentation. These events are time coded relative to the media timeline of the media presentation and might represent, for example, the appearance of a particular cast member or playback of a particular music track. The video frames of the media presentation are processed to identify visually similar intervals that may serve as or be used to identify contexts (e.g., scenes) within the media presentation. Relationships between the event data and the visually similar intervals or contexts are used to identify portions of the media presentation during which the occurrence of additional meaningful events is unlikely. This information may be surfaced to a human operator tasked with annotating the content as an indication that part of the media presentation may be skipped.