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