USB20 CAMERA SOFTWARE DRIVER
Schettini, “A multi-task CNN framework for driver face monitoring,” in IEEE International Conference on Consumer Electronics (ICCE-Berlin, Berlin, 2018), pp. Andriyanov, “Pattern recognition on radar images using augmentation,” in Proceedings-2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020 (IEEEE, 2020), pp. ICPR International Workshops and Challenges.
USB20 CAMERA SOFTWARE SOFTWARE
Andriyanov, “First step towards creating a software package for detecting the dangerous states during driver eye monitoring,” in Pattern Recognition. Andriyanov, “Analysis of the acceleration of neural networks inference on intel processors based on OpenVINO Toolkit,” in 2020 Systems of Signal Synchronization, Generating, and Processing in Telecommunications, SYNCHROINFO 2020 (IEEE, 2020). The proposed algorithm requires an additional increase in the accuracy and completeness of recognition of the closed eyes. This uses a simple camera with a low resolution of 640 × 480 pixels. The developed software package allows us to detect closed eyes with precision and recall of about 90%. To develop the program, the Python programming language was used, the Jupyter Notebook was chosen as the development environment, and OpenCV was used as the main library, since it allows us to receive and process data from a USB camera. Different illumination characteristics have resulted in different accuracy rates for each eye. Moreover, the left and right eyes are analyzed separately. Learning occurs in two eye states: open and closed. Such networks training takes place on the eyes cut out from images of faces. However, convolutional neural networks are used to recognize eye conditions. This allows the algorithm to work in real time. Face detection is based on the Viola–Jones method and Haar cascades. The primary attention is paid to the development of a software package that can be used in the future as a system for monitoring the condition of drivers. This article explores the use of computer vision for recognizing human fatigue by the eyes.
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