Research on Gait-Based Human Identification

摘要：

Gait recognition refers to automatic identification of individual based on his/her style of walking. This paper proposes a gait recognition method based on Continuous Hidden Markov Model with Mixture of Gaussians (G-CHMM). First, a Gaussian mix model is initialized for training image sequence with K-means algorithm, and then training the HMM parameters using Baum-Welch algorithm. These gait feature sequences can be trained and obtains a Continuous HMM for every person; therefore, every persons gait sequence can be represented by the 7 keyframes and HMM. The experiments, utilizing CASIA gait databases, present a comparatively correction identification ratio and a comparatively robustness when the bodily angle varying.

关键词： gait recognition hidden markov model gaussian mix model features extraction

作者: XiLing Zhao YongQiang Du

作者单位: Department of Computer Science, Xinyang Agricultural College, Xinyang, china Department of Computer Science, Xinyan aricultural College, Xinyang, china

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 480-482

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）