The Application of Improved FCM Clustering Algorithm in Behavior Recognition

摘要：

　　Diversity,relevance and ambiguity of human behavior have caused great difficulties for behavior recognition.This paper proposes an improved FCM clustering algorithm for the problem that when clustering and modeling of behavioral characteristic descriptors in behavior recognition,the traditional FCM algorithm can not determine the number of clusters.The algorithm is based on the indexes of inter-cluster compactness and the separation of clusters to determine the initial cluster centers.Then model behavioral descriptors that have been clustered to reach the purpose of improving behavior recognition accuracy.The experimental results show that: the improved algorithm can classify and model behavioral descriptors better and improve the recognition accuracy.

关键词： FCM clustering algorithm Number of clusters Cluster validity index Behavior recognition

作者: Yun LIU Jin SHAO

作者单位: Qingdao University of Science and Technology,China

会议类型: 国内会议

会议名称: 2014年国际计算机科学与软件工程学术会议

会议地点: 杭州

会议语种:英文

页码: 1-7

在线出版日期: 2014-10-18（万方平台首次上网日期，不代表论文的发表时间）