IROS 2007: Detection and Tracking of Multiple Pedestrians

Xiaowei Shao, Huijing Zhao, Katsuyuki Nakamura, Kyoichiro Katabira, Ryosuke Shibasaki and Yuri Nakagawa

Abstract:
We propose a novel system for tracking multiple
pedestrians in a crowded scene by exploiting single-row laser
range scanners that measure distances of surrounding objects.
A walking model is built to describe the periodicity of the
movement of the feet in the spatial-temporal domain, and a
mean-shift clustering technique in combination with spatialtemporal
correlation analysis is applied to detect pedestrians.
Based on the walking model, particle filter is employed to track
multiple pedestrians. Compared with camera-based methods,
our system provides a novel technique to track multiple pedestrians
in a relatively large area. The experiments, in which over
300 pedestrians were tracked in 5 minutes, show the validity
of the proposed system.