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Proceedings Paper

Human recognition by body shape features
Author(s): Ming Du; Ling Guan
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Paper Abstract

Non-invasive biometrics is of particular importance because of its application under surveillance environment. Although traditional research in this field is mostly focused on gait recognition, feature based on human body shape is one of the alternate choices we can rely on. Here we propose a body shape based identification system, trying to explore the its distinguishing power in biometrics. Robust image processing procedures such as Wiener filter are implemented to extract binary silhouettes from frontal-view human walking video. The Kalman filter, usually adopted as a powerful tool to facilitate tracking in computer vision applications, here functions as a reliable estimator to recover body shape information from the corrupted observations. The dynamically extracted static feature vectors are then compared to templates to achieve identification. We provide experimental results to demonstrate the performance of our system.

Paper Details

Date Published: 18 March 2005
PDF: 11 pages
Proc. SPIE 5666, Human Vision and Electronic Imaging X, (18 March 2005); doi: 10.1117/12.585119
Show Author Affiliations
Ming Du, Ryerson Univ. (Canada)
Ling Guan, Ryerson Univ. (Canada)


Published in SPIE Proceedings Vol. 5666:
Human Vision and Electronic Imaging X
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Scott J. Daly, Editor(s)

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