{"title":"基于三维几何特征的面部美研究","authors":"Wenming Han, Fangmei Chen, Fuming Sun","doi":"10.1109/PRML52754.2021.9520726","DOIUrl":null,"url":null,"abstract":"Facial beauty is related to different kinds of features, such as geometry, texture and expression. Geometric features are the most investigated ones, because 1) they have clear and interpretable definitions; 2) they do not change with face make-up, illumination and resolution; and 3) they can be used to guide the aesthetic plastic surgeries. Due to the high cost of 3D scanning, most existing works focus on 2D geometric features extracted from frontal face images. However, the profile information is neglected, which also plays an important role in facial beauty judgment. In this paper, we reconstruct 3D faces from 2D images using recent monocular 3D face reconstruction method. Then 22 anatomical landmarks are defined on the 3D face, and based on which totally 51 geometric features are extracted. Finally, we design experiments to evaluate the effectiveness of these features. The results show that ratio features are the most influential ones, and lips also affect facial beauty. Comparison between Asian and Caucasian shows that there are significant differences between different ethnic groups. For Asian faces, an angle feature related to face width and nose height has the highest ranking. For the Caucasian groups, the top-ranked features are length and ratio features, and the lip region plays an important role.","PeriodicalId":429603,"journal":{"name":"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Facial Beauty Study Based on 3D Geometric Features\",\"authors\":\"Wenming Han, Fangmei Chen, Fuming Sun\",\"doi\":\"10.1109/PRML52754.2021.9520726\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Facial beauty is related to different kinds of features, such as geometry, texture and expression. Geometric features are the most investigated ones, because 1) they have clear and interpretable definitions; 2) they do not change with face make-up, illumination and resolution; and 3) they can be used to guide the aesthetic plastic surgeries. Due to the high cost of 3D scanning, most existing works focus on 2D geometric features extracted from frontal face images. However, the profile information is neglected, which also plays an important role in facial beauty judgment. In this paper, we reconstruct 3D faces from 2D images using recent monocular 3D face reconstruction method. Then 22 anatomical landmarks are defined on the 3D face, and based on which totally 51 geometric features are extracted. Finally, we design experiments to evaluate the effectiveness of these features. The results show that ratio features are the most influential ones, and lips also affect facial beauty. Comparison between Asian and Caucasian shows that there are significant differences between different ethnic groups. For Asian faces, an angle feature related to face width and nose height has the highest ranking. For the Caucasian groups, the top-ranked features are length and ratio features, and the lip region plays an important role.\",\"PeriodicalId\":429603,\"journal\":{\"name\":\"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRML52754.2021.9520726\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning (PRML)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRML52754.2021.9520726","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Facial Beauty Study Based on 3D Geometric Features
Facial beauty is related to different kinds of features, such as geometry, texture and expression. Geometric features are the most investigated ones, because 1) they have clear and interpretable definitions; 2) they do not change with face make-up, illumination and resolution; and 3) they can be used to guide the aesthetic plastic surgeries. Due to the high cost of 3D scanning, most existing works focus on 2D geometric features extracted from frontal face images. However, the profile information is neglected, which also plays an important role in facial beauty judgment. In this paper, we reconstruct 3D faces from 2D images using recent monocular 3D face reconstruction method. Then 22 anatomical landmarks are defined on the 3D face, and based on which totally 51 geometric features are extracted. Finally, we design experiments to evaluate the effectiveness of these features. The results show that ratio features are the most influential ones, and lips also affect facial beauty. Comparison between Asian and Caucasian shows that there are significant differences between different ethnic groups. For Asian faces, an angle feature related to face width and nose height has the highest ranking. For the Caucasian groups, the top-ranked features are length and ratio features, and the lip region plays an important role.