Abstract
This paper demonstrates how appearance adaptive models can be employed for real-time object tracking using particle swarm optimization. The parallelization of the code is done using OpenMP directives and SSE instructions. We show the performance of the algorithm that was evaluated on multi-core CPUs. Experimental results demonstrate the performance of the algorithm in comparison to our GPU based implementation of the object tracker using appearance-adaptive models. The algorithm has been tested on real image sequences.
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Rymut, B., Kwolek, B. (2011). Parallel Appearance-Adaptive Models for Real-Time Object Tracking Using Particle Swarm Optimization. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23938-0_46
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DOI: https://doi.org/10.1007/978-3-642-23938-0_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23937-3
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