Key Frame Extraction for Video Summarization Using Motion Activity Descriptors

Abstract

Summarization of a video involves providing a gist of the entire video without affecting the semantics of the video. This has been implemented by the use of motion activity descriptors which generate relative motion between consecutive frames. Correctly capturing the motion in a video leads to the identification of the key frames in the video. This motion in the video can be obtained by using block matching techniques which is an important part of this process. It is implemented using two techniques, Diamond Search and Three Step Search, which have been studied and compared. The comparison process is tried across various videos differing in category, content, and objects. It is found that there is a trade-off between summarization factor and precision during the summarization process.