A New Robust Pupil Detection Algorithm for Eye Tracking Based Human-Computer Interface
| Autor: | Gabriel Bonteanu, Radu Gabriel Bozomitu, Arcadie Cracan, Petronela Bonteanu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Pixel
Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Ellipse 01 natural sciences Pupil Running time Robustness (computer science) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Eye tracking 020201 artificial intelligence & image processing Detection rate 010306 general physics Algorithm |
| Zdroj: | 2019 International Symposium on Signals, Circuits and Systems (ISSCS). |
| DOI: | 10.1109/isscs.2019.8801818 |
| Popis: | In this paper a new pupil detection algorithm appropriate for development of head mounted eye tracking interfaces is presented. The robustness of the proposed algorithm is given by its low running time and the ability to accurately provide the coordinates of the pupil center even under real-world scenarios like variable illumination and high noise conditions. The proposed algorithm is based on an adaptive quantitative binarization technique with a feedback-loop controlled threshold. The pupil center is detected by applying the Least Square Fit to Ellipse procedure to the processed eye image. The performance of this algorithm is given by a 5 pixels detection rate of 93%, obtained for the eye images from two representative databases. |
| Databáze: | OpenAIRE |
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