Eye Localization Using Convolutional Neural Networks and Image Gradients

  • Werton P. de Araujo
  • Thelmo P. de Araujo UECE
  • Gustavo A. L. de Campos UECE


Eye detection is a preprocessing step in many methods using facial images. Some algorithms to detect eyes are based on the characteristics of the gradient flow in the iris-sclera boundary. These algorithms are usually applied to the whole face and a posterior heuristic is used to remove false positives. In this paper, we reverse that approach by using a Convolutional Neural Network (CNN) to solve a regression problem and give a coarse estimate of the eye regions, and only then do we apply the gradient-based algorithms. The CNN was combined with two gradient-based algorithms and the results were evaluated regarding their accuracy and processing time, showing the applicability of both methods for eye localization.


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DE ARAUJO, Werton P.; DE ARAUJO, Thelmo P.; DE CAMPOS, Gustavo A. L.. Eye Localization Using Convolutional Neural Networks and Image Gradients. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 15. , 2018, São Paulo. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 140-149. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2018.4411.