Human Behavior Classification Using Thinning Algorithm and Support Vector Machine

被引：2

作者：

Widyanto, M. Rahmat ^{[1
]}

Endah, Sukmawati Nur ^{[2
]}

Hirota, Kaoru ^{[3
]}

机构：

[1] Univ Indonesia, Fac Comp Sci, Depok Campus, Depok 16424, Indonesia

[2] Diponegoro Univ, Fac Math & Nat Sci, Tembalang, Semarang, Indonesia

[3] Tokyo Inst Technol, Dept Computat Intelligence & Syst Sci, Midori Ku, Yokohama, Kanagawa 2268502, Japan

来源：

JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2010年 / 14卷 / 01期

关键词：

support vector machine; thinning algorithm;

D O I：

10.20965/jaciii.2010.p0028

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a skeleton-based human behavior classification system using thinning algorithm and Support Vector Machine (SVM). The proposed system consists of two phases, skeletonization phase where main human body part is constructed using thinning algorithm, and classification phase where the skeleton constructed by previous phase is classified into certain human behavior pose using SVM. Experiment using 44 training and 44 testing data of real human poses shows that the system achieves 81.06% accuracy. This system can be further developed for early detection of criminal action.

引用

页码：28 / 33

页数：6

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