Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20783
Title: Dynamic selection and effective compression of key frames for video abstraction
Authors: Zhang, XD
Liu, TY
Lo, KT 
Feng, J
Keywords: Clustering and video abstraction
Key frame selection
Motion compensation
Issue Date: 2003
Publisher: North-Holland
Source: Pattern recognition letters, 2003, v. 24, no. 9-10, p. 1523-1532 How to cite?
Journal: Pattern recognition letters 
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.
URI: http://hdl.handle.net/10397/20783
ISSN: 0167-8655
EISSN: 1872-7344
DOI: 10.1016/S0167-8655(02)00391-4
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