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CAIP
2015
Springer

ExCuSe: Robust Pupil Detection in Real-World Scenarios

7 years 10 months ago
ExCuSe: Robust Pupil Detection in Real-World Scenarios
Abstract. The reliable estimation of the pupil position is one the most important prerequisites in gaze-based HMI applications. Despite the rich landscape of image-based methods for pupil extraction, tracking the pupil in real-world images is highly challenging due to variations in the environment (e.g. changing illumination conditions, reflection, etc.), in the eye physiology or due to variations related to further sources of noise (e.g., contact lenses or mascara). We present a novel algorithm for robust pupil detection in real-world scenarios, which is based on edge filtering and oriented histograms calculated via the Angular Integral Projection Function. The evaluation on over 38,000 new, hand-labeled eye images from real-world tasks and 600 images from related work showed an outstanding robustness of our algorithm in comparison to the state-of-the-art. Download link (algorithm and data): https://www.ti.uni-tuebingen.de/
Wolfgang Fuhl, Thomas C. Kübler, Katrin Sippe
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where CAIP
Authors Wolfgang Fuhl, Thomas C. Kübler, Katrin Sippel, Wolfgang Rosenstiel, Enkelejda Kasneci
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