Human-computer Interaction Using Head Movements

This paper presents a real-time gaze direction estimation approach. The face region and facial features are extracted automatically by applying skin detection, gray-scale morphology and a geometrical face model. The Kalman filtering is applied for tracking and estimation of the 3-D pose of the moving head. The rough gaze direction is determined from the orientation of the head. Experiments with real image sequences show that the system is able to extract and track facial features reliably. Also, the gaze position in the computer display can be roughly determined. Theoretical gaze position estimation was tested with synthetic data and promising results were obtained. The high real-time performance achieved indicates that the proposed system can be applied in resource limited embedded systems.