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Related Experiment Videos

Robust pupil center detection using a curvature algorithm.

D Zhu1, S T Moore, T Raphan

  • 1Department of Computer and Information Science, Brooklyn College of the City University of New York, 11210, USA.

Computer Methods and Programs in Biomedicine
|July 1, 1999
PubMed
Summary
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This study introduces a novel algorithm for accurately locating the pupil center in video-based eye tracking. The method uses pupil boundary curvature to overcome common occlusions, improving eye orientation calculations.

Area of Science:

  • Computer Vision
  • Biomedical Engineering
  • Ophthalmology

Background:

  • Accurate pupil center detection is crucial for eye orientation analysis in video systems.
  • Existing methods struggle with occlusions from eyelids, eyelashes, and reflections, leading to errors.

Purpose of the Study:

  • To develop a robust algorithm for precise pupil center estimation.
  • To overcome limitations of current techniques in handling pupil boundary occlusions.

Main Methods:

  • A new algorithm analyzing pupil boundary curvature characteristics.
  • Identifying and filtering artifacts caused by occlusions using curvature peaks.
  • Fitting remaining boundary points to an ellipse to determine the pupil center.

Main Results:

Keywords:
NASA Discipline NeuroscienceNon-NASA Center

Related Experiment Videos

  • The algorithm effectively eliminates artifacts caused by occlusions.
  • Accurate pupil center estimation is achieved even with less than 40% of the pupil boundary visible.
  • The method demonstrates robustness in challenging conditions.

Conclusions:

  • The developed curvature-based algorithm provides a robust and accurate solution for pupil center detection.
  • This technique significantly improves eye orientation calculations in video-based systems.
  • It offers reliable performance despite partial pupil visibility.