https://scholars.lib.ntu.edu.tw/handle/123456789/559145
標題: | Multi-model fusion on real-time drowsiness detection for telemetric robotics tracking applications | 作者: | REN-CHYUAN LUO Hsu, C.H. Wen, Y.-C. |
公開日期: | 2020 | 卷: | 2020-August | 來源出版物: | International Conference on Advanced Robotics and Intelligent Systems, ARIS | 摘要: | Drowsiness of driver is one of the common causes resulting in road crashes. According to the research, there have been twenty percent of the road accidents which are related to the drowsiness of drivers. Nowadays, with the development technology, various approaches are introduced to detect the drowsiness of drivers. In this paper, we propose a multi-model fusion system which is composed of the three models to capture driver's face and detect drowsiness in the real-time for telemetric robotics tracking applications. The sensor device we used is an RGB camera which is mounted in front of driver to obtain the facial image. Then, we combine the results based on the state of the eye blink, yawn and head deviation to determine whether the driver is drowsy. We test our models to obtain the weighting factors in drowsy value. In the experiment, we show that our system has the high accuracy of detection. © 2020 IEEE. |
URI: | https://www.scopus.com/inward/record.url?eid=2-s2.0-85092550029&partnerID=40&md5=138dd1bdf5d826734da8c3d112f59448 https://scholars.lib.ntu.edu.tw/handle/123456789/559145 |
ISSN: | 23743255 | DOI: | 10.1109/ARIS50834.2020.9205780 | SDG/關鍵字: | Agricultural robots; Highway accidents; Intelligent systems; Roads and streets; Capture drivers; Development technology; Drowsiness detection; High-accuracy; Multi-model fusion; Sensor device; Tracking application; Weighting factors; Robotics |
顯示於: | 電機工程學系 |
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