Real-time human motion analysis for human-robot interaction

This paper introduces a novel real-time human motion analysis system based on hierarchical tracking and inverse kinematics. This work constitutes a first step towards our goal of implementing a mechanism of human-machine interaction that allows a robot to provide feedback to a teacher in an imitation learning framework. In particular, we have developed a computer-vision based, upper-body motion analysis system that works without special devices or markers. Since such system is unstable and can only acquire partial information because of self-occlusions and depth ambiguity, we have employed a model-based pose estimation method based on inverse kinematics. The resulting system can estimate upper-body human postures with limited perceptual cues, such as centroid coordinates and disparity of head and hands.