{"title":"利用皮肤纹理特征进行性别识别:一项实验评估","authors":"F. Bianconi, F. Smeraldi, M. Abdollahyan, P. Xiao","doi":"10.1109/IPTA.2016.7821018","DOIUrl":null,"url":null,"abstract":"Skin appearance is almost universally the object of gender-related expectations and stereotypes. This not with standing, remarkably little work has been done on establishing quantitatively whether skin texture can be used for gender discrimination. We present a detailed analysis of the skin texture of 43 subjects based on two complementary imaging modalities afforded by a visible-light dermoscope and the recently developed Epsilon sensor for capacitive imaging. We consider an array of established texture features in combination with two supervised classification techniques (1-NN and SVM) and a state-of-the-art unsupervised approach (t-SNE). A statistical analysis of the results suggests that skin microtexture carries very little information on gender.","PeriodicalId":123429,"journal":{"name":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"On the use of skin texture features for gender recognition: An experimental evaluation\",\"authors\":\"F. Bianconi, F. Smeraldi, M. Abdollahyan, P. Xiao\",\"doi\":\"10.1109/IPTA.2016.7821018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Skin appearance is almost universally the object of gender-related expectations and stereotypes. This not with standing, remarkably little work has been done on establishing quantitatively whether skin texture can be used for gender discrimination. We present a detailed analysis of the skin texture of 43 subjects based on two complementary imaging modalities afforded by a visible-light dermoscope and the recently developed Epsilon sensor for capacitive imaging. We consider an array of established texture features in combination with two supervised classification techniques (1-NN and SVM) and a state-of-the-art unsupervised approach (t-SNE). A statistical analysis of the results suggests that skin microtexture carries very little information on gender.\",\"PeriodicalId\":123429,\"journal\":{\"name\":\"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"volume\":\"127 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA.2016.7821018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA.2016.7821018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the use of skin texture features for gender recognition: An experimental evaluation
Skin appearance is almost universally the object of gender-related expectations and stereotypes. This not with standing, remarkably little work has been done on establishing quantitatively whether skin texture can be used for gender discrimination. We present a detailed analysis of the skin texture of 43 subjects based on two complementary imaging modalities afforded by a visible-light dermoscope and the recently developed Epsilon sensor for capacitive imaging. We consider an array of established texture features in combination with two supervised classification techniques (1-NN and SVM) and a state-of-the-art unsupervised approach (t-SNE). A statistical analysis of the results suggests that skin microtexture carries very little information on gender.