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Proceedings Paper

Gait recognition system based on (2D)2 PCA and HMM
Author(s): Jianqiang Huang; Zhengming Yi; Xiaoying Wang; Huan Wu
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Paper Abstract

In order to carry on the gait recognition fast and effectively, a novel gait recognition based on (2D)2 PCA and HMM is proposed in this paper . Firstly, establish a stable background model by using the adaptive background modeling and get the goal of human motion by using background subtraction. As for the existence of the shadow of the human body and inanity, this article makes shadow detection and elimination by using color space conversion respectively and handles human target image soothingly by using regional filling and morphological filtering on smoothing. the number of high-dimensional video images is high, uses the (2D)2PCA features extracted to reduce the dimensions so as to solve the curse of dimensionality, makes use of HMM to classification training of Gait features extracted, then the classification results are analyzed. This gait recognition system is achieved loading OpenCV under VC++6.0 visual library. Our experimental results demonstrate that the method is effective and has achieved a good recognition effect on CASIA gait database including three different multi-views.

Paper Details

Date Published: 29 August 2016
PDF: 8 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003310 (29 August 2016); doi: 10.1117/12.2244848
Show Author Affiliations
Jianqiang Huang, Qinghai Univ. (China)
Zhengming Yi, Qinghai Univ. (China)
Xiaoying Wang, Qinghai Univ. (China)
Huan Wu, Qinghai Univ. (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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