TOTAL BREGMAN DIVERGENCE FOR MULTIPLE OBJECT TRACKING

In this paper we propose a multi-target tracking based on the tracking-by-detection paradigm. The problem is casted as a discrete association problem where a cost is assigned to each detection-tracklet pair and the evolution of many factors such as position, speed and appearance is observed. As new tracklets enter the scene their appearance is modeled using covariance matrices equipped with the total Bregman divergence to perform the comparisons and robust model updates. Our method provides near-state of the art results in terms of accuracy and is able to execute in real-time.

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