Tracklet Association by Online Target-Specific Metric Learning and Coherent Dynamics Estimation

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In this paper, we present a novel method based on online target-specific metric learning and coherent dynamics estimation for tracklet (track fragment) association by network flow optimization in long-term multi-person tracking.

• Our proposed framework aims to exploit appearance and motion cues to prevent identity switches during tracking and to recover missed detections.
• Furthermore, target-specific metrics (appearance cue) and motion dynamics (motion cue) are proposed to be learned and estimated online, i.e.
• during the tracking process.