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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 347497, 11 pages
http://dx.doi.org/10.1155/2015/347497
Research Article

Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

1Department of Precision Mechanical Engineering, Shanghai University, Shanghai 200072, China
2Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong
3College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China

Received 16 June 2014; Accepted 3 September 2014

Academic Editor: Shouming Zhong

Copyright © 2015 Yazhe Tang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents a novel surveillance system named thermal omnidirectional vision (TOV) system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.