2023/03/13 by Xinrui Chen, Chen, Xinrui, Bingquan Zhang +1
Psychology · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Sleep and Work-Related Fatigue
paper · pdf · doi:10.48550/arxiv.2303.12727
openalex publication_date 2023/03/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.