ExCuSe: Robust Pupil Detection in Real-World Scenarios

  • Wolfgang FuhlEmail author
  • Thomas Kübler
  • Katrin Sippel
  • Wolfgang Rosenstiel
  • Enkelejda Kasneci
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9256)


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):


Edge Image Edge Pixel White Point Pupil Center Threshold Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Wolfgang Fuhl
    • 1
    Email author
  • Thomas Kübler
    • 1
  • Katrin Sippel
    • 1
  • Wolfgang Rosenstiel
    • 1
  • Enkelejda Kasneci
    • 1
  1. 1.Eberhard Karls Universität TübingenTübingenGermany

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