Abstract
We propose a novel people detection method using a Locus-based Probabilistic Occupancy Map (LPOM). Given the calibration data and the motion edges extracted from all views, the method is able to compute the probabilistic occupancy map for the targets in the scene. We integrate the algorithm into a Bayesian-based tracker and do experiments with challenging video sequences. Experimental results demonstrate the robustness and high-precision of the tracker when tracking multiple people in the presence of clutters and occlusions.
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Hu, T., Mutlu, S., Lanz, O. (2013). Multicamera People Tracking Using a Locus-based Probabilistic Occupancy Map. In: Petrosino, A. (eds) Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41184-7_70
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DOI: https://doi.org/10.1007/978-3-642-41184-7_70
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