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Efficiency and robustness are the two most important issues for multiobject tracking algorithms in real-time intelligent video surveillance systems. We propose a novel 2.5-D approach to real-time multiobject tracking in crowds, which is formulated as a maximum aposteriori estimation problem and is approximated through an assignment step and a location step. Observing that the occluding object is...
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