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An Approach to Real-Time Color-based Object Tracking

Memon, M. A. and Angelov, Plamen and Ahmed, H. (2006) An Approach to Real-Time Color-based Object Tracking. In: Evolving Fuzzy Systems, 2006 International Symposium on. IEEE, pp. 81-87. ISBN 0-7803-9718-5

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Abstract

Object tracking is of great interest in different areas of industry, security and defense. Tracking moving objects based on color information is more robust than systems utilizing motion cues. In order to maintain the lock on the object as the surrounding conditions vary, the color model needs to be adapted in real-time. In this paper an on-line learning method for the color model is implemented using fuzzy adaptive resonance theory (ART). Fuzzy ART is a type of neural network that is trained based on competitive learning principle. The color model of the target region is regularly updated based on the vigilance criteria (which is a threshold) applied to the pixel color information. The target location in the next frame is predicted using evolving extended Takagi-Sugeno (exTS) model to improve the tracking performance. The results of applying exTS for prediction of the position of the moving target were compared with the usually used solution based on Kalman filter. The experiments with real footage demonstrate over a variety of scenarios the superiority of the exTS as a predictor comparing to the Kalman filter. Further investigation concentrates on using evolving clustering for realizing computationally efficient simultaneous tracking of different segments in the object (c) IEEE Press

Item Type: Contribution in Book/Report/Proceedings
Additional Information: ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 56234
Deposited By: ep_importer_pure
Deposited On: 19 Jul 2012 17:18
Refereed?: No
Published?: Published
Last Modified: 10 Apr 2014 01:16
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/56234

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