Subject-independent natural action recognition

被引：0
|
作者：
Ren, HB [1 ]
Xu, GY [1 ]
Kee, SC [1 ]
机构：
[1] Samsung Adv Inst Technol, Beijing 100081, Peoples R China
来源：
SIXTH IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION, PROCEEDINGS | 2004年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper Primitive-based Dynamic Bayesian Networks are proposed for subject-independent natural action recognition. Inferred by high-level knowledge, Primitives are distinctive features that describe the context information and the motion information representing human action as well as pose. Dynamic Bayesian Networks could fuse multi-information so that many kinds of weak information could function as strong information for inference. The experimental results show that Primitive-based Dynamic Bayesian Networks not only increase the recognition rate but also improve the robustness.
引用
收藏
页码：523 / 528
页数：6
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