Tai-Chi Chuan Motion Tracking by Integrating Inertial and Monocular Visual Sensors

Abstract

In this paper, we study the 3-D human posture tracking problem for computer-aided Tai-Chi Chuan motion learning. A model-based human motion tracking method is proposed which uses a monocular visual sensor and multiple accelerometers attached to different body parts of a subject. In order to track human postures robustly, a generic complete and parametrically continuous (CPC) kinematic model is constructed. Twelve CPC parameters are adapted according to the lengths of the upper limbs and the joint positions of the shoulders and the thighs so that the generic CPC model can be used to track different subjects. Equations for predicting the acceleration measurements are derived using the kinematic model. A method for assessing the difference between the measured and the predicted silhouette images is provided. The particle filter is adopt to track human posture from torso toward the ends of the limbs. Real experiments have been conducted to test the proposed method with various human motions including five simple actions and a fundamental Tai-Chi Chuan actions (i.e., “ward off”, “roll back”, “press”, and “push”). The results show that the proposed method is very promising.