Appropriate Segment Extraction from Shots Based on Temporal Patterns of Example Videos

Abstract

Videos are composed of shots, each of which is recorded continuously by a camera, and video editing can be considered as a process of re-sequencing shots selected from original videos. Shots usually include redundant segments, which are often edited out by professional editors. This paper proposes a method for automatically extracting appropriate segments to be included in edited videos from shots based on temporal patterns of audio and visual features in appropriate segments and redundant segments in example videos learned with Hidden Markov Models. The effectiveness of the proposed method is verified with experiments using original shots extracted from movies and appropriate segments extracted from movie trailers as example videos.