Classifying Human Body Postures by a Support Vector Machine with Two Simple Features

被引：0

作者：

Nguyen Van Tao ^{[1
]}

Nong Thi Hoa ^{[1
]}

Quach Xuan Truong ^{[1
]}

机构：

[1] Thai Nguyen Univ Informat & Commun Technol, Quyet Thang, Thai Nguyen, Vietnam

来源：

ADVANCES IN INFORMATION AND COMMUNICATION TECHNOLOGY | 2017年 / 538卷

关键词：

Posture classification; Human behaviour analysis; Support Vector Machine; RECOGNITION;

D O I：

10.1007/978-3-319-49073-1_21

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Human behaviour analysis helps to monitor a person's daily activities and detect home care emergencies. Classifying posture is an important step of human behaviour analysis. Many studies improve the accuracy of classifying. However, the number of features is big or extracting these features uses complicated formulas. Therefore, we proposed two features with simple computing. Two new features are formulated from the height and the square showing the human body's silhouettes. Then, we choose a non-linear Support Vector Machine to classify postures based on proposed features. Experiments show Support Vector Machine classify effectively and better than other methods.

引用

页码：188 / 196

页数：9

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