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Conventional cell tracking methods detect multiple cells in each frame(detection) and then associate the detection results in successive time-frames(association). Most cell tracking methods perform the association taskindependently from the detection task. However, there is no guarantee ofpreserving coherence between these tasks, and lack of coherence may adverselyaffect tracking performance. In this paper, we propose the Motion and PositionMap (MPM) that jointly represents both detection and association for not onlymigration but also cell division. It guarantees coherence such that if a cellis detected, the corresponding motion flow can always be obtained. It is asimple but powerful method for multi-object tracking in dense environments. Wecompared the proposed method with current tracking methods under variousconditions in real biological images and found that it outperformed thestate-of-the-art (+5.2\% improvement compared to the second-best).

MPM: Joint Representation of Motion and Position Map for Cell Tracking