Abstract
The difficulties of eye location are mainly caused by the variations of intrinsic eye pattern characteristics from people to people, scale, pose, glasses frame, illumination, etc. To prevail from these problems, this paper addresses a novel and precise robust eye location method. It employs appearance based Bayesian framework to relive the effect of uneven illumination. The appearance of eye patterns is represented by 2D Haar wavelet. It also employs a sophisticated merging and arbitration strategy in order to manage the variations in geometrical characteristics of ambient eye regions due to glasses frames, eye brows, and so on. The located eye candidates are merged or eliminated according to the merging rule. If the merged regions are more than one, we apply the arbitration strategy. The arbitration strategy is based on a minimizing energy function by probabilistic forces and image forces that pull it toward eyes. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously proposed methods.
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Koh, E.J., Rhee, P.K. (2006). Merging and Arbitration Strategy for Robust Eye Location. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11892960_69
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DOI: https://doi.org/10.1007/11892960_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46535-5
Online ISBN: 978-3-540-46536-2
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