Abstract
In the current decade, many automobile crashes are occurred due to the non-professional drivers and the negligence of legal drivers during driving. To reduce the automobile crashes, illegal driver recognition and legal driver’s attention estimation requires significant research attention in the field of computer vision. In this paper, a driver recognition and assistance system is proposed to monitor the driver’s attention and drowsiness based on face and eyes tracking. For that, initially, the driver is recognized before starting the automobile through SVM, where features are extracted by using uniform LBP and Gabor filters. After recognize the driver, the driver is allowed to drive. Furthermore, from the recognized face, the eye’s pupils are detected and tracked to estimate the attention of the driver. Here, color feature is utilized to track the face and eyes through the mean shift algorithm. The system generates the alarm for the illegal driver and awareness alarm of the driver in the case of driver face angle and eye’s fatigue. The effectiveness of the proposed system is demonstrated through the real-time experiment. The proposed system is evaluated in the different lighting conditions and presented outcomes demonstrate the adequacy.
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Khaliluzzaman, M., Ahmed, S., Jashim Uddin, M. (2022). A Vision-Based Real-Time Driver Identity Recognition and Attention Monitoring System. In: Karuppusamy, P., Perikos, I., García Márquez, F.P. (eds) Ubiquitous Intelligent Systems. Smart Innovation, Systems and Technologies, vol 243. Springer, Singapore. https://doi.org/10.1007/978-981-16-3675-2_55
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DOI: https://doi.org/10.1007/978-981-16-3675-2_55
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