SYSTEMS AND METHODS FOR SEMANTICALLY CLASSIFYING AND NORMALIZING SHOTS IN VIDEO

摘要

The present disclosure relates to systems and methods for classifying videos based on video content. For a given video file including a plurality of frames, a subset of frames is extracted for processing. Frames that are too dark, blurry, or otherwise poor classification candidates are discarded from the subset. Generally, material classification scores that describe type of material content likely included in each frame are calculated for the remaining frames in the subset. The material classification scores are used to generate material arrangement vectors that represent the spatial arrangement of material content in each frame. The material arrangement vectors are subsequently classified to generate a scene classification score vector for each frame. The scene classification results are averaged (or otherwise processed) across all frames in the subset to associate the video file with one or more predefined scene categories related to overall types of scene content of the video file.

主权项

1. A method comprising:
within each frame of a sequence of video frames, for each spatial segment of a plurality of spatial segments within the frame, determining likelihoods of the spatial segment corresponding to specific types of contents; based on the likelihoods, generating arrangement data for each frame in the sequence, the arrangement data representing a spatial arrangement of the specific types of contents within the frame; identifying groups of consecutive video frames, within the sequence, that have similar arrangement data; based on the identified groups of consecutive video frames, identifying start times and end times for scenes within a video, the video comprising the video frames.