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An effective video shot boundary detection method based on supervised learning

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1 Author(s)
Yongliang Xiao ; Dept. of Inf. Manage., Hunan Coll. of Finance & Econ., Changsha, China

Video shot boundary detection plays an every important role in video processing. It is the first step toward video content analysis and content-based video retrieval. We develop a novel approach for video shot boundary detection based on supervised learning. Our method consists in first extracting video frame feature using a supervised kernel non-locality preserving projections, then video frames are split into abrupt transitions, gradual transitions or normal frames using two cascaded Localized-SVM classifiers. Experimental results show the effectiveness of our method.

Published in:

Advanced Computer Control (ICACC), 2010 2nd International Conference on  (Volume:4 )

Date of Conference:

27-29 March 2010

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