Abstract
Multiple-target tracking represents a challenging question in uncontrolled scenarios. Due to high-level applications, such as behavioral analysis, the need of a robust tracking system is high. In a multiple tracking scenario it is necessary to consider and resolve occlusions, as well as formations and splitting of object groups. In this work, a method based in a hierarchical architecture for multiple tracking is proposed to deal with these matters. Background subtraction, blob detection, low-level tracking, collision detection and high-level appearance tracking is used to avoid occlusion and grouping problems. Experimental results show promising results in tracking management, grouping, splitting, occlusion events, while remains invariant to illumination changes.
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Cancela, B., Ortega, M., Penedo, M.G., Fernández, A. (2011). Solving Multiple-Target Tracking Using Adaptive Filters. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21593-3_42
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DOI: https://doi.org/10.1007/978-3-642-21593-3_42
Publisher Name: Springer, Berlin, Heidelberg
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