Robust pupil center detection using a curvature algorithm

Determining the pupil center is fundamental for calculating eye orientation in video-based systems. Existing techniques are error prone and not robust because eyelids, eyelashes, corneal reflections or shadows in many instanc es occlude the pupil. We have developed a new algorithm which utilizes curv ature characteristics of the pupil boundary to eliminate these artifacts. P upil center is computed based solely on points related to the pupil boundar y. For each boundary point, a curvature value is computed. Occlusion of the boundary induces characteristic peaks in the curvature function. Curvature values for normal pupil sizes were determined and a threshold was found wh ich together with heuristics discriminated normal from abnormal curvature. Remaining boundary points were fit with an ellipse using a least squares er ror criterion. The center of the ellipse is an estimate of the pupil center . This technique is robust and accurately estimates pupil center with less than 40% of the pupil boundary points visible. (C) 1999 Elsevier Science Ir eland Ltd. All rights reserved.