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《Transactions of Beijing Institute of Technology》 2006-01
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Support Vector Machine(SVM) Meta Classifier Based Sport Video Classification

ZHANG Long-fei~1,CAO Yuan-da~1,ZHOU Yi-hua~1,LI Jian~2 (1.School of Computer Science and Technology,Beijing Institute of Technology,Beijing 100081,China;2.Department of Computer Science,Beijing University of Post and Telecommunication,Beijing 100876,China)  
A novel SVM meta classifier based sport video classification algorithm is presented to bridge the low level feature and high level semantic feature.Domain knowledge rules are exploited to extract features semantically.Meta classifiers classify the video clips with combination strategies.The experimental results showed that the algorithm can be used in almost all sports video classification,and have better performance than other non-semantic associate classification algorithms with an accuracy attaining 92.23%.
【CateGory Index】: TP391.41
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