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Support vector machine meta classifier based sport video classification

  • Long Fei Zhang*
  • , Yuan Da Cao
  • , Yi Hua Zhou
  • , Jian Li
  • *此作品的通讯作者
  • Beijing Institute of Technology
  • Beijing University of Posts and Telecommunications

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

A support vector machine (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%.

源语言英语
页(从-至)41-44+67
期刊Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
卷26
期1
出版状态已出版 - 1月 2006

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