Automatic eye detection using intensity and edge information

We propose a new algorithm to detect the pupils of both eyes from a human face in an intensity image. First, feature points which are the candidates for the pupils of both eyes are extracted from the face image by using the feature template proposed by Lin and Wu (see IEEE Trans. Image Processing, vol.8, no.6, p.834-45 (1999). Next, the proposed algorithm computes a cost for each pair of feature points satisfying a spatial constraint. The cost is computed by searching for a circular region corresponding to the iris around each feature point. Finally, the algorithm determines a pair of feature points with the smallest cost to be the pupils of both eyes. As a result of the experiment using all faces without spectacles in the face database of the University of Bern, the success rate of the proposed algorithm was 93.0% on the average. Also, if looking-down faces are excluded, the success rate of the proposed algorithm was 97.1% on the average