Real-time drowsiness evaluation system using marker-less facial motion capture

Abstract

This paper proposes a drowsiness expression rating system that can rate drowsiness in real time using only video information. Drowsiness in drivers is caused by various factors, including driving on monotonous roads, and can lead to numerous problems, e.g., traffic accidents. Previously, we developed an offline drowsiness evaluation system the uses only video image information from MediaPipe, which is a marker-less facial motion capture system. The proposed system can perform real-time drowsiness rating on multiple platforms and requires a smartphone or personal computer. Results of applied to car driving demonstrate that the accuracy of the proposed system was 89.7%, 78.8%, and 65.0% for binary, three-class, and five-class classification tasks, respectively. In addition, the proposed system outperformed existing systems in binary, three-class, and five-class classification tasks by 6.0%, 0.8%, and 4.3%, respectively. These results demonstrate that the proposed system exhibits a higher accuracy rate than the existing methods.