The ability to capture the direction the eyes point in while the subject is a distance away from the camera offers the potential for intuitive human-computer interfaces, allowing for a greater interactivity, more intelligent HCI behavior, and increased flexibility. In this paper, we present a two-camera system that detects the face from a fixed, wide-angle camera, estimates a rough location for the eye region using an eye detector based on topographic features, and directs another active pan-tilt-zoom camera to focus in on this eye region. We also propose a novel eye gaze estimation approach for point-of-regard (PoG) tracking on a large viewing screen. To allow for greater head pose freedom, we developed a new calibration approach to find the 3D eyeball location, eyeball radius, and fovea position. Moreover, we map both the iris center and iris contour points to the eyeball sphere (creating a 3D iris disk) to get the optical axis; we then rotate the fovea accordingly and compute our final, visual axis gaze direction. We intend to integrate this gaze estimation approach with our two-camera system, permitting natural, non-intrusive, pose-invariant PoG estimation in distance and allowing user translational freedom without resorting to infrared or complex hardware setups such as stereo-cameras or “smart rooms.”
['Michael Reale', 'Terry Hung', 'Lijun Yin']
Pointing with the eyes: Gaze estimation using a static/active camera system and 3D iris disk model