A method of head pose estimation based on Active Shape Model and stereo vision

Abstract

This paper presents a method of head pose estimation based on Active Shape Model (ASM) and stereo vision. The relationship between image coordinate system and global coordinate system is outlined in order to get prepared for mapping key landmarks from the former one to the latter one. We utilize Active Shape Model to locate 77 facial landmarks in both left and right images, and implement stereo matching by obtaining disparities directly from the landmarks in the same polar lines. The advantages of the algorithm in accuracy and real-time are manifested by experiments. The head pose is decomposed into pith, yaw and roll, and we use geometric relationship between facial landmarks and the angle around each axis of global coordinate system to estimate head pose. In addition, roll angle compensation method is brought up to expand roll detection range. Finally, we verify the rationality of our proposed head pose estimation method by experiments.