Abstract
In this paper, we propose a new method for pupil localization in images. The main contribution of the proposed method is twofold. Firstly, the method is based on the proposed eye model that takes into account physiological properties of eyes (i.e. reflects the properties of pupil, iris, and sclera). Secondly, the correct shape and the position of the model are determined using an evolutionary algorithm called Self-Organizing Migrating Algorithm (SOMA). Thanks to these ideas, the proposed method is faster than the state-of-the-art methods without reduction of accuracy. We evaluated the algorithms on two publicly available data sets in remote tracking scenarios (namely BioID [7] and GI4E [11]).
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Acknowledgments
This work was partially supported by Grant of SGS No. SP2018/42, VŠB - Technical University of Ostrava, Czech Republic.
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Fusek, R., Dobeš, P. (2020). Pupil Localization Using Self-organizing Migrating Algorithm. In: Zelinka, I., Brandstetter, P., Trong Dao, T., Hoang Duy, V., Kim, S. (eds) AETA 2018 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application. AETA 2018. Lecture Notes in Electrical Engineering, vol 554. Springer, Cham. https://doi.org/10.1007/978-3-030-14907-9_21
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