Spatio temporal Consistency and Hierarchical Matching for Multi Target Multi Camera Vehicle Tracking
Recently, many approaches have been addressed to realize Multi Target Multi Camera(MTMC) vehicle tracking, which is critical in intelligent transportation system (ITS) Continuous improvements of MTMC have been limited by two modules trajectory feature representation and feature metric in the city scale camera condition. In this paper, we propose a spatio temporal consistency and hierarchical matching method to overcome the challenges. As first step, a popular object detection and object tracking method are implemented to detect vehicles and track them in single camera, thus achieved high performance. The smoothness of trajectory and slice direction of movement make spatiotemporal consistency more confident. As second step, a bottom up hierarchical match strategy is used to match targets in different cameras. Top performance in City Scale Multi Camera Vehicle Tracking task at the NVIDIA AI City Challenge 2019 demonstrated the advantage of our methods.
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