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- W2149244199 abstract "This paper demonstrates, to our best knowledge, the first attempt on gender and ethnicity identification from silhouetted face profiles using a computer vision technique. The results achieved, after testing on 441 images, show that silhouetted face profiles have a lot of information, in particular, for ethnicity identification. Shape context based matching was employed for classification. The test samples were multi-ethnic. Average accuracy for gender was 71.20% and for ethnicity 71.66%. However, the accuracy was significantly higher for some classes, such as 83.41% for females (in case of gender identification) and 80.37% for East and South East Asians (in case of ethnicity identification)." @default.
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- W2149244199 date "2009-11-01" @default.
- W2149244199 modified "2023-09-26" @default.
- W2149244199 title "Gender and ethnicity identification from silhouetted face profiles" @default.
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- W2149244199 doi "https://doi.org/10.1109/icip.2009.5414117" @default.
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