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A Driver Fatigue Detection Algorithm Based on Dynamic Tracking of Small Facial Targets Using YOLOv7

Shugang LIU, Yujie WANG, Qiangguo YU, Jie ZHAN, Hongli LIU, Jiangtao LIU

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Summary :

Driver fatigue detection has become crucial in vehicle safety technology. Achieving high accuracy and real-time performance in detecting driver fatigue is paramount. In this paper, we propose a novel driver fatigue detection algorithm based on dynamic tracking of Facial Eyes and Yawning using YOLOv7, named FEY-YOLOv7. The Coordinate Attention module is inserted into YOLOv7 to enhance its dynamic tracking accuracy by focusing on coordinate information. Additionally, a small target detection head is incorporated into the network architecture to promote the feature extraction ability of small facial targets such as eyes and mouth. In terms of compution, the YOLOv7 network architecture is significantly simplified to achieve high detection speed. Using the proposed PERYAWN algorithm, driver status is labeled and detected by four classes: open_eye, closed_eye, open_mouth, and closed_mouth. Furthermore, the Guided Image Filtering algorithm is employed to enhance image details. The proposed FEY-YOLOv7 is trained and validated on RGB-infrared datasets. The results show that FEY-YOLOv7 has achieved mAP of 0.983 and FPS of 101. This indicates that FEY-YOLOv7 is superior to state-of-the-art methods in accuracy and speed, providing an effective and practical solution for image-based driver fatigue detection.

Publication
IEICE TRANSACTIONS on Information Vol.E106-D No.11 pp.1881-1890
Publication Date
2023/11/01
Publicized
2023/08/21
Online ISSN
1745-1361
DOI
10.1587/transinf.2023EDP7093
Type of Manuscript
PAPER
Category
Image Recognition, Computer Vision

Authors

Shugang LIU
  Hunan University of Science and Technology
Yujie WANG
  Hunan University of Science and Technology
Qiangguo YU
  Huzhou College
Jie ZHAN
  Hunan University of Science and Technology
Hongli LIU
  Hunan University
Jiangtao LIU
  Hunan University of Science and Technology

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