Corpus ID: 212713143

Detecting Fatigue Driving Through PERCLOS: A Review

@inproceedings{Kim2020DetectingFD,
  title={Detecting Fatigue Driving Through PERCLOS: A Review},
  author={Samuel Kim and Irfan Wisanggeni and Ryan Ros and Rania Hussein},
  year={2020}
}
In this paper, we present a literature survey about drowsy driving detection using PERCLOS metric that determines the percentage of eye closure. This metric determines that an eye is closed if the percentage of eye closure is 80% or above. When this percentage is observed for multiple frames of a video camera feed, the driver is determined to be in an unsafe fatigue status. In our research, we found that the PERCLOS metric had a 0.79 to 0.87 correlation coefficient value which exceeds the 0.7 R… Expand

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