Eyes Segmentation Applied to Gaze Direction and Vigilance Estimation
Abstract
An efficient algorithm to iris segmentation and its application to automatic and non-intrusive gaze tracking and vigilance estimation is presented and discussed. A luminance gradient technique is used to fit the irises from face images. A robust preprocessing which mimics the human retina is used in such a way that a robust system to luminance variations is obtained and contrast enhancement is achieved. The validation of the proposed algorithm is experimentally demonstrated by using three well-known test databases: the FERET database, the Yale database and the Cohn-Kanade database. Experimental results confirm the effectiveness and the robustness of the proposed approach to be applied successfully in gaze direction and vigilance estimation.
BibTeX
@conference{Hammal-2005-120283,author = {Zakia Hammal and Corentin Massot and Guillermo Bedoya and Alice Caplier},
title = {Eyes Segmentation Applied to Gaze Direction and Vigilance Estimation},
booktitle = {Proceedings of Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science},
year = {2005},
month = {August},
volume = {3687},
pages = {236 - 246},
}