Human Action Recognition Based on Fuzzy Support Vector Machines

摘要：

As human action is uncertain and illegible, a human action recognition method basing on fuzzy support vector machine is presented. Fuzzy support vector machine employs the membership function to solve the unclassifiable areas which happens the traditional SVMs two-class problems extend to the multi-class problems. The method is evaluated on the Weizmann action dataset and received comparative high correct recognition rate. The experimental results show that our approach has efficient recognition performance.

关键词： computer vision human action recognition membership function fuzzy support vector machine

作者: Kan Li

作者单位: Network Management Center Shandong Polytechnic University Jinan,China

会议类型: 国际会议

会议名称: 2012 Fifth International Symposium on Computational Intelligence and Design 第五届计算智能与设计国际会议 ISCID 2012

会议地点: 杭州

会议语种:英文

页码: 45-48

在线出版日期: 2012-10-28（万方平台首次上网日期，不代表论文的发表时间）