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Face mask detection algorithm based on HSV+HOG features and SVM 被引量:6
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作者 HE Yumin WANG Zhaohui +2 位作者 GUO Siyu YAO Shipeng HU Xiangyang 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2022年第3期267-275,共9页
To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machine... To automatically detecting whether a person is wearing mask properly,we propose a face mask detection algorithm based on hue-saturation-value(HSV)+histogram of oriented gradient(HOG)features and support vector machines(SVM).Firstly,human face and five feature points are detected with RetinaFace face detection algorithm.The feature points are used to locate to mouth and nose region,and HSV+HOG features of this region are extracted and input to SVM for training to realize detection of wearing masks or not.Secondly,RetinaFace is used to locate to nasal tip area of face,and YCrCb elliptical skin tone model is used to detect the exposure of skin in the nasal tip area,and the optimal classification threshold can be found to determine whether the wear is properly according to experimental results.Experiments show that the accuracy of detecting whether mask is worn can reach 97.9%,and the accuracy of detecting whether mask is worn correctly can reach 87.55%,which verifies the feasibility of the algorithm. 展开更多
关键词 hue-saturation-value(hsv)features histogram of oriented gradient(HOG)features support vector machine(SVM) face mask detection feature point detection
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