Pose estimation of multiple people using contour features from multiple laser range finders

Laser based tracking systems have been developed for mobile robotics and intelligent surveillance areas. Existing systems estimate only human positions. In this paper, we propose a method for human pose estimation represented by human head and waist position using only laser range finders. Two features of human cross-sectional contours are extracted from laser scanner data scanning on the height of waist. This method estimates human pose by using these features in the Bayesian filtering framework. Moreover, we develop a new particle filter framework with two transition models and two resampling steps. In this framework, position estimation and pose estimation are performed by many hypotheses. Our experimental results demonstrate the effectiveness of the method in pose estimation of multiple people by using only several laser scanners.