Comparative Study of Human Gait by Using Video Motion Capture System

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Abstract:

This paper, by using German Simi Motion walking motion system, quantitatively describes the parameters and indicators of the human gait characteristics, tracks and captures the characteristics of body movement and motions of articulation points, compares the gait characteristics between different people, conclude significant differences between walking gait characteristics corresponding to different leg heights and knee bending angles through a large number of experiments, and finds out a description of stability and diversity under different human gait characteristics. This study extends the range and ideas of biological personal identification technology research, so as to provide a more scientific description of gait characteristics, so this study sets a basis for personal identification and establishing identity by using gait characteristics.

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290-294

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June 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Zhang Congjun, Liu Yinong, Xiao Lihua. Probability and Mathematical Statistics [M]. Shanghai, Fudan University Press. (2006).

Google Scholar

[2] Li Shiming, Shi Fengli. Contrastive Analysis for Sports Biomechanics of Different Walking Postures [J]. Journal of Tianjin Institute of Physical Education, 2007, 22 (6): 504-508.

Google Scholar

[3] Wang Yan, Analysis of Human Body's Lower Limbs Movement. [D]. Da Lian: Dalian University of Technology, (2005).

Google Scholar

[4] Liu Long, Zhang Jianguo. Application of Three-dimensional Photograph Measuring System in Analysis of Human Body's Upper Limbs Movement. [J]. Journal of Tianjin Institute of Light Industry, 2003, 18 (1): 51-53.

Google Scholar

[5] Liu Guoyi. Human Motion Capture Based on Video [D]. Beijing: Institute of Computing Technology of the Chinese Academy of Sciences, (2002).

Google Scholar

[6] Sidenbladh H, Black M, Fleet D·Stochastic tracking of 3D human figures using 2D image motion [C]/Proceedings of European Conference on Computer Vision, Dublin, 2000: 702-718.

DOI: 10.1007/3-540-45053-x_45

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