Abstract
This paper presents a visual system for real-time eye detection and tracking in the near-infrared (NIR) video streams for drivers’ monitoring. The system starts with crude eye position estimation based on an eye model suitable for NIR processing. In the next step, eye regions are verified with the classifier operating in the higher-order decomposition of the tensor of eye prototypes. Finally, the process is augmented with the linear tracker which facilitates eye detection and allows real-time operation necessary in the automotive environment. The reported experiments show high accuracy and real-time operation of the system in the car.
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Acknowledgments
This work was supported by the Polish National Science Center under the grant no. DEC-2013/09/B/ST6/02264 and AGH Statutory Funds no. 11.11.230.017. The author is very grateful to Mr. Marcin Bugaj, as well as to Mr. Stanisław Groński and Krzysztof Groński for their help in the experiments.
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Cyganek, B. (2016). Real-Time Eye Detection and Tracking in the Near-Infrared Video for Drivers’ Drowsiness Control. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_45
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DOI: https://doi.org/10.1007/978-3-319-26227-7_45
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