期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：7
页码：117-126
DOI：10.14257/ijsip.2016.9.7.11
出版社：SERSC
摘要：The performance of video automatic classification algorithm depends largely on the extraction of video features and selection of classification algorithm. From the perspective of video contents and video style type, the paper presents a new feature representation scheme, i.e. MPEG-7 visual description sub-combination model, a new method based on support vector machine (SVM) to solve problems with existing algorithms, by analyzing visual differences between five types of videos. Also we improve the classifier decision scheme and then propose the secondary prediction mechanism based on SVM 1-1 approach, improving the accuracy of SVM multi-classification method. The experimental results indicate that the proposed method manifests differences of different videos about feature selection, enhances the discrimination ability of videos pending for classification and increases the effectiveness of SVM multi-video classification.
关键词：video classification; feature; support vector machine
