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Smart city article details

Title	Traffic-Aware Multi-Camera Tracking Of Vehicles Based On Reid And Camera Link Model
ID_Doc	58684
Authors	Hsu H.-M.; Wang Y.; Hwang J.-N.
Year	2020
Published	MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia
DOI	http://dx.doi.org/10.1145/3394171.3413863
Abstract	Multi-target multi-camera tracking (MTMCT), i.e., tracking multiple targets across multiple cameras, is a crucial technique for smart city applications. In this paper, we propose an effective and reliable MTMCT framework for vehicles, which consists of a traffic-aware single camera tracking (TSCT) algorithm, a trajectory-based camera link model (CLM) for vehicle re-identification (ReID), and a hierarchical clustering algorithm to obtain the cross camera vehicle trajectories. First, the TSCT, which jointly considers vehicle appearance, geometric features, and some common traffic scenarios, is proposed to track the vehicles in each camera separately. Second, the trajectory-based CLM is adopted to facilitate the relationship between each pair of adjacently connected cameras and add spatio-temporal constraints for the subsequent vehicle ReID with temporal attention. Third, the hierarchical clustering algorithm is used to merge the vehicle trajectories among all the cameras to obtain the final MTMCT results. Our proposed MTMCT is evaluated on the CityFlow dataset and achieves a new state-of-the-art performance with IDF1 of 74.93%. © 2020 ACM.
Author Keywords	camera link model; hierarchical clustering; MTMCT; multi-camera tracking; traffic-aware single camera tracking; vehicle reid

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