A Multi-Cue-Based Human Body Tracking System

Abstract

This paper presents a real-time vision-based system for the tracking of human upper body with both color images and depth maps. We combine the color-histogram-based particle filtering and mean shift algorithm to track face and hands and estimate other body parts by human kinetics. A multi-cue approach that integrates depth information and the color-based method is introduced to handle the rapid and complex motions of human hands. Real-time depth is recovered based on simple hardware configuration, which makes our system easy to be popularized in many real-world applications like digital entertainment. The system runs at 20 fps for images with 320x240 pixels on a 2.8GHz PC.