Abstract
By using the knowledge of facial structure and temperature distribution, this paper proposes an automatic eye localization method from infrared thermal images. A facial structure consisting of 15 sub-regions is proposed to extract Haar-like features. Eight classifiers are learned from the features selected by Adaboost algorithm for left and right eye, respectively. A vote strategy is used to find the most likely eyes. Experimental results on the NVIE and Equinox databases show the effectiveness of our approach. © 2013 Springer-Verlag.
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Wang, S., Shen, P., & Liu, Z. (2013). Eye localization from infrared thermal images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7742 LNAI, pp. 35–42). https://doi.org/10.1007/978-3-642-37081-6_5
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