Gait Identification Based on Hidden Markov Model

被引：0

作者：

Zhao, XiLing ^{[1
]}

Shang, XinHua ^{[1
]}

机构：

[1] Xinyang Agr Coll, Dept Comp Sci, Xinyang, Peoples R China

来源：

2012 2ND INTERNATIONAL CONFERENCE ON APPLIED ROBOTICS FOR THE POWER INDUSTRY (CARPI) | 2012年

关键词：

Gait recognition; Hidden Markov Model; K-means Algorithm; Overflow; RECOGNITION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes a gait recognition method based on Continuous Hidden Markov Model with Mixture of Gaussians (G-CHMM). First, we initialize a Gaussian mix model for training image sequence with K-means algorithm, then train the HMM parameters using a Baum-Welch algorithm. Improved training process can be solved arithmetic overflow. Finally, the recognition is achieved by HMM. The experiments made on CASIA gait databases obtain comparatively high correction identification ratio and comparatively strong robustness for variety of bodily angle.

引用

页码：812 / 815

页数：4

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