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Pupil Localization Using Geodesic Distance

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Advances in Visual Computing (ISVC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11241))

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Abstract

The main contributions of the presented paper can be summarized as follows. Firstly, we introduce a unique and robust dataset of human eyes that can be used in many detection and recognition scenarios, especially for the recognition of driver drowsiness, gaze direction, or eye-blinking frequency. The dataset consists of approximately 85,000 different eye regions that were captured using various near-infrared cameras, various resolutions, and various lighting conditions. The images are annotated into many categories. Secondly, we present a new method for pupil localization that is based on the geodesic distance. The presented experiments show that the proposed method outperforms the state-of-the-art methods in this area.

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Acknowledgments

This work was partially supported by Grant of SGS No. SP2018/42, VŠB - Technical University of Ostrava, Czech Republic.

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Authors and Affiliations

  1. FEECS, Department of Computer Science, Technical University of Ostrava, 17. listopadu 15, 708 33, Ostrava-Poruba, Czech Republic

    Radovan Fusek

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  1. Radovan Fusek
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Correspondence to Radovan Fusek .

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Editors and Affiliations

  1. University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, USA

    Richard Boyle

  3. University of Nevada, Reno, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, USA

    Darko Koracin

  5. DARPA, Arlington, USA

    Matt Turek

  6. University of Utah, Salt Lake City, USA

    Srikumar Ramalingam

  7. National University of Defense Technology, Changsha, China

    Kai Xu

  8. Microsoft Research Asia, Beijing, China

    Stephen Lin

  9. Bosch Research, Farmington Hills, MI, USA

    Bilal Alsallakh

  10. University of North Carolina at Charlotte, Charlotte, USA

    Jing Yang

  11. Microsoft Research, Redmond, USA

    Eduardo Cuervo

  12. University of Colorado at Colorado Springs, Colorado Springs, USA

    Jonathan Ventura

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Fusek, R. (2018). Pupil Localization Using Geodesic Distance. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2018. Lecture Notes in Computer Science(), vol 11241. Springer, Cham. https://doi.org/10.1007/978-3-030-03801-4_38

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  • DOI: https://doi.org/10.1007/978-3-030-03801-4_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03800-7

  • Online ISBN: 978-3-030-03801-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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