On-Road Pedestrian Tracking Across Multiple Moving Cameras

Abstract

With the rapid development of autonomous driving, tracking on-road pedestrians raises more attention in the public. Currently, most researches focus on single camera based tracking or tracking across multiple static cameras. Tracking across multiple moving cameras has not been well studied yet. In this paper, we propose a workflow for tracking pedestrians across multiple moving cameras, leveraging the state-of-the-art single camera based tracking method of FairMOT. We consider different factors such as appearance features, motion information, and camera spatial distribution to improve the tracking performance. The experimental results carried on a multi-target multi-moving camera tracking dataset show the feasibility of the proposed scheme in solving the tracking issue in a complex environmental setting.