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Communication Dans Un Congrès Année : 2016

Real-time eye pupil localization using Hough regression forest

Amine Kacete
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Jérôme Royan

Résumé

Eyes are one of the most salient features of the human face, and the location of the pupil allows access to important information which can be used in several computer vision applications. Several commercial eye-trackers can estimate with good accuracy the pupil location, but need complex hardware specifications and a controlled user environment (high eye image resolution, good illumination, small head pose variations) making these solutions difficult to use in an arbitrary environment. In this paper, we present an approach based on Hough randomized regression trees. We demonstrate, by several evaluations on challenging public datasets that our approach is very robust to illumination, scale, eye movements and high head pose variations and yields a significant improvement compared to a wide range of state-of-the-art methods..
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Dates et versions

hal-01393562 , version 1 (09-11-2016)

Identifiants

Citer

Amine Kacete, Renaud Séguier, Jérôme Royan, Michel Collobert, Catherine Soladie. Real-time eye pupil localization using Hough regression forest. IEEE Winter Conference on Applications of Computer Vision (WACV 2016), Mar 2016, Lake Placid, NY, United States. pp.1 - 8, ⟨10.1109/WACV.2016.7477666⟩. ⟨hal-01393562⟩
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