A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection

Bingquan Zhang; Xinrui Chen

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A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection

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arxiv 2303.12727 v1 pith:DCIUX7M2 submitted 2023-03-13 cs.CV

Xinrui Chen , Bingquan Zhang This is my paper

classification cs.CV

keywords fatiguemodelalgorithm-basedaspectfacemouthrateratio

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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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