Abstract
In an infrared (IR) image sequence of human walking the human silhouette can be reliably extracted from the background regardless of lighting conditions and colors of the human surfaces and backgrounds in most cases. Moreover some important regions containing skin such as face and hands can be accurately detected in IR image sequences. In this paper we propose a kinematic based approach for automatic human motion analysis from IR image sequences. The proposed approach estimates 3D human walking parameters by per forming a modifed least squares fit of the 3D kinematic model to the 2D silhouette extracted from a monocular IR image sequence where continuity and symmetry of human walking and detected hand regions are also considered in the optimization function. Experimental results show that the proposed approach achieves good performance in gait analysis with different view angles with respect to the walking direction and is promising for further gait recognition.