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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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Correspondence to Radovan Fusek .

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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

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