Abstract
Drowsiness of the driver is the significant cause of the road accidents. The need of the hour is to come up with some measures to control it, and our prototype helps us to achieve that. The main objective of this research study is to come up with a solution to curb down road accidents due to fatigue. Drowsiness can be detected through various ways, but we mainly focus on facial detection using computer vision. In this prototype, a driver’s face is captured by our program for analyzing. We apply facial landmark points with the help of a facial detection algorithm to extract the location of the driver’s eyes. Subsequently, the eye moment is recorded as per the specified frame; if the driver closes his eyes more frequently or more than a specified time, then he/she can be declared as drowsy which will eventually lead to triggering of the alarm. With the advancement of technology, automatic self-driving cars are emerging at a fast rate, but still, they need someone’s supervision so we can use the above-mentioned technology in those cars to see if a driver is sleepy or not. If he/she is sleepy, then the car can slow down and stop gradually, on its own and will not go further.
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Bhatia, U., Tshering, Kumar, J., Choubey, D.K. (2022). Drowsiness Image Detection Using Computer Vision. In: Sharma, T.K., Ahn, C.W., Verma, O.P., Panigrahi, B.K. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1380. Springer, Singapore. https://doi.org/10.1007/978-981-16-1740-9_55
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DOI: https://doi.org/10.1007/978-981-16-1740-9_55
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