DRIVER FATIGUE DETECTION METHOD BASED ON FACIAL FEATURES BY USING DEEP LEARNING

Authors

  • Sayyad Shahana Author
  • Tadi Kumar Satish Reddy Author
  • Dendukuri Surya Varma Author
  • Kommireddy M K Naga Phanindra Rao, Author
  • Dr. M.Aravind Kumar Author
  • Ch.Ramasrinivas Author

DOI:

https://doi.org/10.62647/

Abstract

Fatigue detection using face recognition, powered by Dlib and CNN, addresses a critical road safety issue by identifying driver fatigue, a major cause of accidents. This system analyzes facial features like eye closure, yawning, and head position to detect early signs of fatigue in real-time. Leveraging Dlib's fast and accurate facial landmark detection, the model continuously monitors the driver and issues alerts when fatigue is detected, enabling timely intervention. Trained on a diverse dataset of facial images, the system ensures high accuracy across various lighting and environmental conditions, offering a cost-effective solution to reduce fatigue-related accidents and enhance road safety.

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Published

23-04-2025

How to Cite

DRIVER FATIGUE DETECTION METHOD BASED ON FACIAL FEATURES BY USING DEEP LEARNING. (2025). International Journal of Information Technology and Computer Engineering, 13(2), 529-531. https://doi.org/10.62647/