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Video shot-boundary detection using singular-value decomposition and statistical tests

[+] Author Affiliations
Zuzana Černeková

Aristotle University of Thessaloniki, Department of Informatics, Artificial Intelligence and Information Analysis Laboratory, Box 451, 54124 Thessaloniki, Greece

Constantine Kotropoulos

Aristotle University of Thessaloniki, Department of Informatics, Artificial Intelligence and Information Analysis Laboratory, Box 451, 54124 Thessaloniki, Greece

Ioannis Pitas

Aristotle University of Thessaloniki, Department of Informatics, Artificial Intelligence and Information Analysis Laboratory, Box 451, 54124 Thessaloniki, Greece

J. Electron. Imaging. 16(4), 043012 (December 07, 2007). doi:10.1117/1.2812528
History: Received January 31, 2007; Revised June 12, 2007; Accepted June 23, 2007; Published December 07, 2007
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We deal with video shot-cut detection in digital videos using the singular-value decomposition (SVD). SVD is performed on a matrix whose columns are the 3D frame color histograms. We have used SVD for its capabilities to derive a refined low-dimensional feature space from the high-dimensional raw feature space, where similar video patterns are placed together and can be easily clustered. After SVD is performed, a two-phase process is employed to detect the shots. In the first phase, a dynamic clustering method is used to create the frame clusters. In the second phase, every two consecutive clusters, obtained by the clustering procedure, are tested for a possible merging in order to reduce false shot-cut detections. In the merging phase, statistical hypothesis testing is used. The detection technique was applied to several TRECVID video test sets that exhibit different types of shots and contain significant object and camera motion inside the shots. We demonstrate that the method detects cuts and gradual transitions, such as dissolves and fades, with high accuracy.

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© 2007 SPIE and IS&T

Topics

Video

Citation

Zuzana Černeková ; Constantine Kotropoulos and Ioannis Pitas
"Video shot-boundary detection using singular-value decomposition and statistical tests", J. Electron. Imaging. 16(4), 043012 (December 07, 2007). ; http://dx.doi.org/10.1117/1.2812528


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