Detection of Head Pose and Gaze Direction for Human-Computer Interaction

In this contribution we extend existing methods for head pose estimation and investigate the use of local image phase for gaze detection. Moreover we describe how a small database of face images with given ground truth for head pose and gaze direction was acquired. With this database we compare two different computational approaches for extracting the head pose. We demonstrate that a simple implementation of the proposed methods without extensive training sessions or calibration is sufficient to accurately detect the head pose for human-computer interaction. Furthermore, we propose how eye gaze can be extracted based on the outcome of local filter responses and the detected head pose. In all, we present a framework where different approaches are combined to a single system for extracting information about the attentional state of a person.