Abstract
This paper presents the development of a fatigue detection system that would be capable of detecting an individual’s level of alertness through live video acquisition. The approach is to build a nonintrusive system that uses computer vision methods to localize face, eyes, and iris positions to measure level of eye closure within an image, which, in turn, can be used to identify visible eye signs associated with fatigue leading to a sleepy state. The aim here is to detect this state early enough and issue a warning or alert in the form of an alarm.
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I would like to thank all who are involved directly or indirectly involved in this research. I would like to acknowledge my students (Mr. Aiman Jalil and Mr. Ravi Rajan) for their immense contribution. I, (Ashis Pradhan) being a first author who is directly involved in this research activities on behalf of all researcher involved state that all data provided are genuine and authorize you to publish this research work.
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Pradhan, A., Sunuwar, J., Sharma, S., Agarwal, K. (2018). Fatigue Detection Based on Eye Tracking. In: Bhattacharyya, S., Chaki, N., Konar, D., Chakraborty, U., Singh, C. (eds) Advanced Computational and Communication Paradigms. Advances in Intelligent Systems and Computing, vol 706. Springer, Singapore. https://doi.org/10.1007/978-981-10-8237-5_12
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DOI: https://doi.org/10.1007/978-981-10-8237-5_12
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