Absolute Head Pose Estimation From Overhead Wide-Angle Cameras

Most surveillance cameras have a wide-angle field of view and are situated unobtrusively in overhead positions. For this type of application, head pose estimation is very challenging because of the limitations of the quality and resolution of the incoming data. In addition, as a person moves, their pose relative to the camera changes, but the desired pose is the absolute pose with respect to the room or space. In this paper, we present a solution to estimate absolute coarse head pose for wide-angle overhead cameras by integrating 3D head position and pose information. The work involves image-based learning, pose correction based on 3D position, and real-time multi-camera integration of low-resolution imagery. The system can be applied to an active face cataloguer to obtain the best view of the face for surveillance, to customer relationship management to record behavior in retail stores or to virtual reality as an input device.