Fatigue detection based on non-contact respiratory detection

Xing Chen; Lumei Su; Min Xu; Bo Deng; Yuanxuan Zhu

doi:10.1117/12.2586893

4 January 2021 Fatigue detection based on non-contact respiratory detection

Xing Chen, Lumei Su, Min Xu, Bo Deng, Yuanxuan Zhu

Proceedings Volume 11605, Thirteenth International Conference on Machine Vision; 116050J (2021) https://doi.org/10.1117/12.2586893
Event: Thirteenth International Conference on Machine Vision, 2020, Rome, Italy

Abstract

Most of current methods for fatigue detection are based on fatigue features extracted from face or head. This paper proposes a novel fatigue detection mode based on non-contact respiratory detection. This paper proposes to use the respiratory rate feature for fatigue detection. Since the appearance of the respiratory rate fatigue feature will be earlier than the facial fatigue feature, fatigue can be predicted early by the respiratory rate. The difficulty of respiratory rate fatigue detection lies in the extraction of respiratory rate features and detection accuracy, so this paper adopts the non-contact respiratory detection based on dense optical flow method to solve the above problems. In this paper, a large number of experimental comparisons between respiratory rate fatigue detection and facial fatigue detection have confirmed that fatigue can be detected faster through respiratory rate fatigue characteristics, but there will still be a small deviation in the detection of respiratory rate, so this paper proposes to compare facial fatigue characteristics with breathing The fatigue detection method combined with the rate of fatigue characteristics, this method greatly improves the accuracy and speed of fatigue detection.

Citation Download Citation

Xing Chen, Lumei Su, Min Xu, Bo Deng, and Yuanxuan Zhu "Fatigue detection based on non-contact respiratory detection", Proc. SPIE 11605, Thirteenth International Conference on Machine Vision, 116050J (4 January 2021); https://doi.org/10.1117/12.2586893

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