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. © 2013 Springer-Verlag.
CITATION STYLE
Hu, T., Mutlu, S., & Lanz, O. (2013). Multicamera people tracking using a locus-based probabilistic occupancy map. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8157 LNCS, pp. 693–702). https://doi.org/10.1007/978-3-642-41184-7_70
Mendeley helps you to discover research relevant for your work.