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arXiv · 2303.12727

A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection

Xinrui Chen·Bingquan Zhang
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Abstract

As fatigue is normally revealed in the eyes and mouth of a person's face, this paper tried to construct a XGBoost Algorithm-Based fatigue recognition model using the two indicators, EAR (Eye Aspect Ratio) and MAR(Mouth Aspect Ratio). With an accuracy rate of 87.37% and sensitivity rate of 89.14%, the model was proved to be efficient and valid for further applications.

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Xinrui Chen, Bingquan Zhang. 2023-03-13. A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection. https://arxiv.org/abs/2303.12727

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