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, we initialize a Gaussian mix model for training image sequence with K-means algorithm, then train the HMM parameters using a Baum-Welch algorithm. These gait feature sequences can be trained and obtain a Continuous HMM for every person, therefore, the 7 key frames and the obtained HMM can represent each person's gait sequence. Finally, the recognition is achieved by Front algorithm. The experiments made on CASIA gait databases obtain comparatively high correction identification ratio and comparatively strong robustness for variety of bodily angle.

Date Published: 19 March 2013
PDF: 5 pages
Proc. SPIE 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 87621Y (19 March 2013); doi: 10.1117/12.2020186

Published in SPIE Proceedings Vol. 8762:
PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering
Honghua Tan, Editor(s)