Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/81573
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Type: Conference paper
Title: Video shot segmentation using graph-based dominant-set clustering
Author: Li, Li
Zeng, Xianling
Li, Xi
Hu, Weiming
Zhu, Pengfei
Citation: Proceedings of the First International Conference on Internet Multimedia Computing and Service, held in Kunming, Yunnan, YT, China, November 23 - 25, 2009; pp.166-169
Publisher: ACM Press
Issue Date: 2009
ISBN: 9781605588407
Conference Name: International Conference on Internet Multimedia Computing and Service (2009 : Kunming, Yunnan)
ICIMCS 2009
School/Discipline: School of Computer Science
Statement of
Responsibility: 
Li Li, Xianglin Zeng, Xi Li, Weiming Hu, Pengfei Zhu
Abstract: Video shot segmentation is a solid foundation for automatic video content analysis, for most content based video retrieval tasks require accurate segmentation of video boundaries. In recent years, using the tools of data mining and machine learning to detect shot boundaries has become more and more popular. In this paper, we propose an effective video segmentation approach based on a dominant-set clustering algorithm. The algorithm can not only automatically determine the number of video shots, but also obtain accurate shot boundaries with low computation complexity. Experimental results have demonstrated the effectiveness of the proposed shot segmentation approach.
Rights: Shot boundary detection; dominant-set clustering
RMID: 0020112700
DOI: 10.1145/1734605.1734645
Published version: http://dl.acm.org/citation.cfm?id=1734645
Appears in Collections:Computer Science publications

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