ST-Gait: A Framework for Human Identification Using Structural and Transitional Characteristics of Gait

Author:

Gupta Anand1,Goel Pragya1

Affiliation:

1. Netaji Subhas Institute of Technology

Abstract

An interesting problem in Biometrics Research is human identification by reliable extraction of anatomical and behavioral patterns of a person from his manner of walking. Till now the identification through the said characteristics has been addressed by mostly using marker-based methods. These methods have limited applications in the area of security, where a person must be ‘marked’ for correct identification. To mitigate this limitation, we propose a marker-less, model- based approach (ST-Gait) for human identification using gait. The proposed method is simple but effective, and involves low computational complexity. It is validated on a well- known benchmark database (gait database A of CASIA). The encouraging experimental results show that the technique achieves an accuracy of 90% and can be a promising tool for human identification in the area of security.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference11 articles.

1. J. H. Clark, A fast scan-line algorithm for rendering parametric surfaces, In Proceedings of SIGGRAPH Computer Graphics, Vol. 13, Issue 2, Pages 174, August (1979).

2. http: /www. csbr. ia. ac. cn/english/Gait%20Databases. asp.

3. M. Ekinci, Human Identification Using Gait, Turk Journal of Electrical Engineering, Vol. 14, No. 2, (2006).

4. A Adam and S. Amershi, Identifying humans by their walk and generating new motions using hidden Markov models, CPSC 532A Topics in AI: Graphical models and CPSC 526 computer animation, December 15, (2004).

5. B. Ye and Y. Wen, A new gait recognition method based on body contour", In Proceedings of 9th International Conference on Control, Automation, Robotics and Vision (ICARCV, 06), Pages 1-6, Singapore, 5-8 December (2006).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3