Facial measurement and analysis is an important part of anthropometry,which provides data support for the design of facial protective equipment.To overcome the inconveniences,low efficiency and poor measurement accura...Facial measurement and analysis is an important part of anthropometry,which provides data support for the design of facial protective equipment.To overcome the inconveniences,low efficiency and poor measurement accuracy of facial size parameters measured and analyzed by manual contact,a method of automatic measurement and analysis of face size parameters is proposed.First,the automatic marking method of faces based on deep learning can improve the efficiency ofmeasuring facial parameters.Then,facial parameters,including nose middle width,nose width,face width and eye width,can be measured.Finally,the data set of face size parameters is classified and counted based on fuzzy clustering analysis.Sixty-five groups of Han youth facial data are collected formeasurement and analysis,and compared with the existing algorithms,the facial morphology analysis system presented in this paper has higher measurement accuracy.展开更多
基金supported in part by the Natural Science Foundation of Heilongjiang Province (No:LH2020F049).
文摘Facial measurement and analysis is an important part of anthropometry,which provides data support for the design of facial protective equipment.To overcome the inconveniences,low efficiency and poor measurement accuracy of facial size parameters measured and analyzed by manual contact,a method of automatic measurement and analysis of face size parameters is proposed.First,the automatic marking method of faces based on deep learning can improve the efficiency ofmeasuring facial parameters.Then,facial parameters,including nose middle width,nose width,face width and eye width,can be measured.Finally,the data set of face size parameters is classified and counted based on fuzzy clustering analysis.Sixty-five groups of Han youth facial data are collected formeasurement and analysis,and compared with the existing algorithms,the facial morphology analysis system presented in this paper has higher measurement accuracy.
