Global Data Association for MultiObject Tracking Using Network Flows Li Zhang Yuan Li and Ramakant Nevatia University of Southern California Institute of Robotics and Intelligent Systems li

zhangyli8nevatia uscedu Abstract We propose a network 64258ow based optimization method for data association needed for multiple object tracking The maximumaposteriori MAP data association prob lem is mapped into a cost64258ow network with a nonoverl

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