Automatic Gait Recognition From a Distance
Gait recognition is an unique biometrics which can identify individuals from a distance where others are incapable. However, nearly all of the algorithms proposed are 2D methods based on studying image sequences captured by a mono-vision. This paper presents an original 3D approach for automatic gait recognition based on analyzing image sequences captured by stereo vision. Contour matching is done after binarized silhouette of a moving individual is firstly achieved in order to get 3D contour. Then, stereo gait feature (SGF) which is the norm of stereo silhouette vector (SSV) is extracted from 3D contour. In addition, Principal Component Analysis (PCA) is adopted for dimensionality reduction. Finally, NN and ENN is applied for classifying and distinguishing. A stereo gait database named PRLAB was established as a training and probing sets for gait recognition based on stereo vision. Experimental result on PRLAB proved the efficiency and robustness of the method.
Gait recognition Stereo vision Principal component analysis Stereo gait feature
Haitao Liu Yang Cao Zengfu Wang
Department of Automation, University of Science and Technology of China, Hefei 230027, China
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
2777-2782
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）