Circularity and Self-Similarity Analysis for the Precise Location of the Pupils

This paper presents a new method to automatically locate pupils in images (even with low-resolution) containing human faces. In particular pupils are localized by a two steps procedure: at first self-similarity information is extracted by considering the appearance variability of local regions and then they are combined with an estimator of circular shapes based on a modified version of the Circular Hough Transform. Experimental evidence of the effectiveness of the method was achieved on challenging databases containing facial images acquired under different lighting conditions and with different scales and poses.