Labeling of human motion by constraint-based genetic algorithm

被引：0
|
作者：
Hu, Fu Yuan [1 ,2 ]
Wong, Han San [1 ]
Liu, Zhi Qiang [3 ]
Qu, Hui Yang [1 ]
机构：
[1] City Univ Hong Kong, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China
[2] Northwestern Polytech Univ, Xian, Peoples R China
[3] City Univ Hong Kong, Sch Creat Media, Hong Kong, Peoples R China
来源：
COMPUTATIONAL INTELLIGENCE AND SECURITY | 2007年 / 4456卷
关键词：
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：
This paper presents a new method to label parts of human body automatically based on the joint probability density function (PDF). To adapt to different motion for different articulation, the probabilistic models of each triangle different number of mixture components with MML are adopted. To solve the computation load problem of genetic algorithm (CA), a constraint-based genetic algorithm (CBGA) is developed to obtain the best global labeling. Our algorithm is developed to report the performance with experiments from running, walking and dancing sequences.
引用
收藏
页码：105 / +
页数：2
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