Head pose estimation with one camera, in uncalibrated environments

Abstract

Head pose together with eye gaze are a reliable indication regarding the estimate of the focus of attention of a person standing in front of a camera, with applications ranging from driver's attention estimation to meeting environments. As gaze indication, eye gaze in non-intrusive or non highly specialized environments is, most times, difficult to detect and, when possible, combination with head pose is necessary. Also, in order to successfully track the rotation angles of the head, a priori knowledge regarding the equipment setup parameters is needed, or specialized hardware, that can be intrusive is required. Here, we propose a novel facial feature tracker that uses Distance Vector Fields (DVFs) and, combined with a new technique for face tracking, successfully detects facial feature positions during an image sequence and estimates head pose parameters. No a priori knowledge regarding camera or environmental parameters is needed for our technique. © 2010 ACM.