Dynamic selection and effective compression of key frames for video abstraction

Authors:
Xu-Dong Zhang;Tie-Yan Liu;Kwok-Tung Lo;Jian Feng
Affiliations:
Multimedia Signal Processing Laboratory, Department of Electronic Engineering, Tsinghua University, Beijing, PR China;Multimedia Signal Processing Laboratory, Department of Electronic Engineering, Tsinghua University, Beijing, PR China;Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;Department of Computer Engineering and Information Technology, City University of Hong Kong, Hong Kong
Venue:
Pattern Recognition Letters
Year:
2003

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Abstract

This paper reports on a new key frame based video abstraction method. With our method, a video sequence is first segmented into a number of video shots. Several key frames are selected in each shot using a dynamic selection technique. For these key frames, a motion-based clustering algorithm is applied so that key frames in the same cluster are alike in sense of motion compensation error, while those from different clusters are quit dissimilar. Then a novel cluster-based coding scheme is developed for efficient representation of the key frames. Simulations show that the proposed method can select key frames according to the dynamics of a video sequence and abstract the video with different levels of scalability.