Abstract
In this paper we propose a particle swarm optimization with resampling for marker-less body tracking. The resampling is employed to select a record of the best particles according to the weights of particles making up the swarm. The algorithm better copes with noise and reduces the premature stagnation. Experiments on 4-camera datasets show the robustness and accuracy of our method. It was evaluated on nine sequences using ground truth provided by Vicon. The full body motion tracking was conducted in real-time on two PC nodes, each of them with two multi-core CPUs with hyper-threading, connected by 1 GigE.
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Kwolek, B., Krzeszowski, T., Gagalowicz, A., Wojciechowski, K., Josinski, H. (2012). Real-Time Multi-view Human Motion Tracking Using Particle Swarm Optimization with Resampling. In: Perales, F.J., Fisher, R.B., Moeslund, T.B. (eds) Articulated Motion and Deformable Objects. AMDO 2012. Lecture Notes in Computer Science, vol 7378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31567-1_9
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DOI: https://doi.org/10.1007/978-3-642-31567-1_9
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