A new method to automatically locate pupils in images (even with low resolution) containing near-frontal human faces is presented. In particular, pupils are localized by an unsupervised procedure consisting of two steps: at first, self-similarity information is extracted by considering the appearance variability of local regions, and then it is 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 and video sequences containing facial images acquired under different lighting conditions and with different scales and poses. (C) 2013 SPIE and IS&T
Unsupervised approach for the accurate localization of the pupils in near-frontal facial images
Leo Marco;Cazzato Dario;De Marco Tommaso;Distante Cosimo
2013
Abstract
A new method to automatically locate pupils in images (even with low resolution) containing near-frontal human faces is presented. In particular, pupils are localized by an unsupervised procedure consisting of two steps: at first, self-similarity information is extracted by considering the appearance variability of local regions, and then it is 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 and video sequences containing facial images acquired under different lighting conditions and with different scales and poses. (C) 2013 SPIE and IS&TI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.