Real-time target tracking through mobile crowdsensing

Abstract

In order to track a single target in real-time across a large area, we proposed a novel method which combines mobile crowdsensing and existing sparse camera networks. Tracking is proceeded by reports, which either come from cameras or smart phone users. Intra-camera tracking is performed on selected cameras to identify target, and smart phone users can report with live photo or text when seeing the target. Such schema can largely help tracking target within blind area and increase the accuracy of target identification, due to the better identification ability of human eyes. Novel validation and correction mechanisms are designed to eliminate false reports, which ensures the robustness of our method. Compared with traditional cross-camera tracking methods, our design can be performed in real-time with better performance even if the target has appearance changes during the tracking. Simulations are done using road structures of our university, which validate the accuracy and robustness of our design.