Multiple-Person Tracking by Multiple Cameras and Laser Range Scanners in Indoor Environments

Abstract

In this paper, we propose a method for multiple-person tracking using cameras and laser range scanners. Our method estimates 3D positions of human body and head, and labels them with their identities. Individual particle filters track person correctly by integrating information from laser range scanners and target-specific information from cameras, thus compensating for weak points of each. We also develop a particle filter framework that tracks the human head simultaneously using the estimated body position. Results of experiments demonstrate the effectiveness and robustness of the proposal in tracking multiple persons with multiple scanners and cameras.