Comparison of Four Kinds of Fuzzy C-means Clustering Methods and Their Applications on Posture Classification

被引：0

作者：

Wang, Chuanxu ^{[1
]}

Yan, Chunjuan ^{[1
]}

机构：

[1] Qingdao Univ Sci & Technol, Fac Informat, Qingdao 266061, Peoples R China

来源：

2009 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION SYSTEMS AND APPLICATIONS, PROCEEDINGS | 2009年

关键词：

fuzzy C-mean; relational fuzzy C-means; NERF C-means; posture classification;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Comparisons of four Fuzzy C-means (FCM) clustering algorithms are analysed, which includes Fuzzy C-means (FCM) and traditional Relational Fuzzy C-means (RFCM) and None Euclidean Relational Fuzzy C-means (NERFCM) and Any Relational Fuzzy C-means (ARFCM). Their common points and different limitations on usage are discussed, finally an optimal clustering algorithm is chosen and its application on human posture classification is implemented, and experiments prove its efficiency and sensitivity.

引用

页码：382 / 385

页数：4

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