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.
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Wang, S., Shen, P., Liu, Z. (2013). Eye Localization from Infrared Thermal Images. In: Schwenker, F., Scherer, S., Morency, LP. (eds) Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction. MPRSS 2012. Lecture Notes in Computer Science(), vol 7742. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37081-6_5
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DOI: https://doi.org/10.1007/978-3-642-37081-6_5
Publisher Name: Springer, Berlin, Heidelberg
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