DocumentCode :
3791044
Title :
Information theory-based shot cut/fade detection and video summarization
Author :
Z. Cernekova;I. Pitas;C. Nikou
Author_Institution :
Dept. of Informatics, Aristotle Univ. of Thessaloniki, Greece
Volume :
16
Issue :
1
fYear :
2006
Firstpage :
82
Lastpage :
91
Abstract :
New methods for detecting shot boundaries in video sequences and for extracting key frames using metrics based on information theory are proposed. The method for shot boundary detection relies on the mutual information (MI) and the joint entropy (JE) between the frames. It can detect cuts, fade-ins and fade-outs. The detection technique was tested on the TRECVID2003 video test set having different types of shots and containing significant object and camera motion inside the shots. It is demonstrated that the method detects both fades and abrupt cuts with high accuracy. The information theory measure provides us with better results because it exploits the inter-frame information in a more compact way than frame subtraction. It was also successfully compared to other methods published in literature. The method for key frame extraction uses MI as well. We show that it captures satisfactorily the visual content of the shot.
Keywords :
"Gunshot detection systems","Data mining","Information theory","Testing","Video sequences","Mutual information","Entropy","Object detection","Motion detection","Cameras"
Journal_Title :
IEEE Transactions on Circuits and Systems for Video Technology
Publisher :
ieee
ISSN :
1051-8215
Type :
jour
DOI :
10.1109/TCSVT.2005.856896
Filename :
1564125
Link To Document :
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