Key frame selection based on Jensen-Rényi divergence

Qing Xu, Xiu Li, Zhen Yang, Jie Wang, Mateu Sbert, Jianfu Li

Abstract: The key frame extraction is designed for obtaining a (very) compressed set of video frames that summarizes the essential content of a video sequence. In this paper, a well-known information theoretic measure, the Jensen-Rényi divergence (JRD), is studied to estimate the frame-by-frame distance between consecutive video images, for segmenting shots/subshots and for choosing key frames. Our new key frame extraction method, which is effective and computationally fast, contributes to a good and quick understanding of a large amount of video data.