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- W2899973923 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." @default.
- W2899973923 created "2018-11-16" @default.
- W2899973923 creator A5021785261 @default.
- W2899973923 date "2018-01-01" @default.
- W2899973923 modified "2023-10-06" @default.
- W2899973923 title "Pupil Localization Using Geodesic Distance" @default.
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- W2899973923 doi "https://doi.org/10.1007/978-3-030-03801-4_38" @default.
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