关键词: 体育视频, 最小二乘支持向量机, 分器设计, 特征提取, 证据理论

Abstract: The correct rate of sports video classification for single feature is very low and stability is poor, this paper proposes a sports video classification method combining Least Squares Support Vector Machine（LSSVM） with evidence theory（DS-LSSVM）. The color, texture, brightness, motion vector features of sports video are extracted, and then the extracted features are input into LSSVM to learn and get the preliminary classification results which are taken as evidence to establish the basic probability assignment, and DS is used to decide level fusion, the final sports video classification results are got according to the classification threshold, the simulation experiment is carried out. The simulation results show that the classification rate of the proposed algorithm reaches 97.90%, compared with the reference algorithms, the proposed algorithm has high video classification rate and good stability advantages.

Key words: sports video, least squares support vector machine, classifier design, feature extraction, evidence theory