Head pose estimation of partially occluded faces

Abstract

This paper describes an algorithm, which calculates the approximate head pose of partially occluded faces without training or manual initialization. The presented approach works on low-resolution Webcam images. The algorithm is based on the observation that for small depth rotations of a head the rotation angles can be approximated linearly. It uses the CamShift (continuous adaptive mean shift) algorithm to track the users head. With a pyramidal implementation of an iterative Lucas-Kanade optical flow algorithm, a certain feature point in the face is tracked. Pan and tilt of the head are estimated from the shift, of the feature point relative to the center of the head. 3D position and roll are estimated from the CamShift, results.