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一篇多摄像头多目标跟踪的文章被IEEE TIP接收


2020-02-26

题为《Multi-Target Multi-Camera Tracking by Tracklet-to-Target Assignment》的文章被IEEE TIP接收

恭喜宇航、魏星博士和石伟伟博士

 

题目

基于跟踪段-目标分配机制的跨摄像头多目标跟踪

Multi-Target Multi-Camera Tracking by Tracklet-to-Target Assignment

作者

贺宇航#、魏星#、洪晓鹏*、石伟伟、龚怡宏

Yuhang He#, Xing Wei#, Xiaopeng Hong*, Weiwei Shi, Yihong Gong

亮点

突破传统方法中跟踪段-跟踪段分配,转变为跟踪段-目标分配的跨摄像头数据关联新方法

 

摘要

   This paper focuses on the Multi-Target Multi-Camera Tracking task (MTMCT), which aims at tracking multiple targets within a multi-camera network. As the trajectory of each target is inherently split into multiple sub-trajectories (namely local tracklets) in a multi-camera network, a major challenge of MTMCT is how to accurately match the local tracklets generated within each camera across different cameras and generate a complete global trajectory for each target, i.e., the cross-camera tracklet matching problem. We solve the cross-camera tracklet matching problem by TRACklet-to-Target Assignment (TRACTA), and propose the Restricted Non-negative Matrix Factorization (RNMF) algorithm to compute the optimal assignment solution that meets a set of constraints, which should be in force in practice. TRACTA can correct the tracking errors caused by occlusions and missed detections in local tracklets, and produce a complete global trajectory for each target across all the cameras. Moreover, we also develop an analytical way of estimating the total number of targets in the camera network, which plays an important role to compute the tracklet-to-target assignment. Experimental evaluations and ablation studies on four MTMCT benchmark datasets show the superiority of the proposed TRACTA method.