Single view head pose estimation

Abstract

This work addresses the problem of human head pose estimation from single view images. 3D rigid head pose is estimated combining Active Appearance Models(AAM) with Pose from Orthography and Scaling with ITerations(POSIT). AAM shape landmarks are tracked over time and used in POSIT for pose estimation. A statistical anthropometric 3D model is used as reference. Several experiences were performed comparing our approach with a planar ground truth. It was achieved average standard deviations about 2 degrees in orientation and 1 centimeter in distance.