Kernel particle filter for real-time 3D body tracking in monocular color images

This paper presents the application of a kernel particle filter for 3D body tracking in a video stream acquired from a single uncalibrated camera. Using intensity-based and color-based cues as well as an articulated 3D body model with shape represented by cylinders, a real-time body tracking in monocular cluttered image sequences has been realized. The algorithm runs at 7.5 Hz on a laptop computer and tracks the upper body of a human with two arms. First, experimental results show that the proposed approach has good tracking as well as recovering capabilities despite using a small number of particles. The approach is intended for use on a mobile robot to improve human robot interaction