A novel SVM-based method for moving video objects recognition

Authors:
Xiaodong Kong;Qingshan Luo;Guihua Zeng
Affiliations:
Laboratory of Coding and Communication Security, Shanghai Jiaotong University, Shanghai, PR China;Laboratory of Coding and Communication Security, Shanghai Jiaotong University, Shanghai, PR China;Laboratory of Coding and Communication Security, Shanghai Jiaotong University, Shanghai, PR China
Venue:
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Year:
2007

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Abstract

A novel method for moving video objects recognition is presented in this paper. In our method, support vector machine (SVM) is adopted to train the recognition model. With the trained model, the moving video objects can be recognized based on the shape features extraction. Comparing with the traditional methods, our method is faster, more accurate and more reliable. The experimental results show the competitiveness of our method.