Abstract
In this paper, we propose a novel template updating modeling algorithm inspired by human brain memory model. Three memory spaces are defined according to the human brain three-stage memory theory. The three memory spaces are used to store the current estimated template and the historical templates. To simulate the memorization process of human brain, such as information updating or exchanging, some behaviors and rules are also defined. The proposed memory-based template updating mechanism can remember or forget what the target appearance has ever been, which helps the tracker adapt to the variation of an object’s appearance more quickly. Experimental results show that the proposed algorithm can handle sudden appearance changes and occlusions robustly when tracking moving objects under complex background by particle filter.
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© 2012 Springer-Verlag Berlin Heidelberg
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Qi, Y., Wang, Y., Xue, T. (2012). Brain Memory Inspired Template Updating Modeling for Robust Moving Object Tracking Using Particle Filter. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds) Advances in Brain Inspired Cognitive Systems. BICS 2012. Lecture Notes in Computer Science(), vol 7366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31561-9_12
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DOI: https://doi.org/10.1007/978-3-642-31561-9_12
Publisher Name: Springer, Berlin, Heidelberg
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