DocumentCode :
595093
Title :
Key frame selection based on Jensen-Rényi divergence
Author :
Qing Xu ; Xiu Li ; Zhen Yang ; Jie Wang ; Sbert, Mateu ; Jianfu Li
Author_Institution :
Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
1892
Lastpage :
1895
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.
Keywords :
data compression; feature extraction; image segmentation; image sequences; video coding; JRD; Jensen-Rényi divergence; content summarization; frame-by-frame distance; information theoretic measure; key frame extraction; key frame selection; subshot segmentation; video frame compressed set; video images; video sequence; Cameras; Educational institutions; Entropy; Information theory; Measurement; Pattern recognition; Video sequences;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460524
Link To Document :
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