Bayesian fusion of laser and vision for multiple People Detection and tracking

Abstract

We present a promising system to simultaneously detect and track multiple humans in the outside scene using laser and vision. The useful information of laser and vision is automatically extracted and combined in a Bayesian formulation. In order to compute MAP estimation, an effective probabilistic detection-based particle filter (PD-PF) has been proposed. Experiments and evaluations demonstrate that not only can our system perform robustly in real environments, but also obtain better approximation of MAP than previous methods in most complex situations.