Multi-Object Tracking and Occlusion Reasoning Based on Adaptive Weighing Particle Filter

Chenguang Liu () and Heng-Da Cheng ()
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Chenguang Liu: Computer Science Department, Utah State University, 403 Old Main Hill, Logan, Utah 84322, USA
Heng-Da Cheng: Computer Science Department, Utah State University, 403 Old Main Hill, Logan, Utah 84322, USA

New Mathematics and Natural Computation (NMNC), 2014, vol. 10, issue 03, 225-238

Abstract: Multi-object tracking has significant merit to our society. However, interactions among objects result in complex spatial occlusions, which gives rise to a challenging problem in tracking. We propose an adaptive weighing particle filter (AWPT) for tracking multiple objects and reasoning the occlusions among them. A weighing-occlusion modeling-weighing procedure is developed to adaptively weigh the particles. Moreover, we propose a stack occlusion model and define the operations on it to maintain the occlusion relationship. The experiments exhibit that the proposed method can effectively track fully occluded objects and reason about the occlusion relationships among them.

Keywords: Multi-object tracking; occlusion handling; occlusion model; particle filter (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1142/S1793005714500136

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