Abstract
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%.
Original language | English |
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Pages (from-to) | 41-44+67 |
Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
Volume | 26 |
Issue number | 1 |
Publication status | Published - Jan 2006 |
Keywords
- Domain knowledge rules
- Meta classifier
- Sports video classification
- Support vector machine
- Video classification