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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3JMPBEE
Repositorysid.inpe.br/sibgrapi/2015/06.19.23.17
Last Update2015:06.19.23.17.15 (UTC) tatiane.leite@gmail.com
Metadatasid.inpe.br/sibgrapi/2015/06.19.23.17.15
Metadata Last Update2020:02.19.02.14.04 (UTC) administrator
Citation KeyLeiteMart:2015:ImAtFa
TitleImproving the attractiveness of faces in images
FormatOn-line
Year2015
Access Date2021, Dec. 07
Number of Files1
Size6394 KiB
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Author1 Leite, Tatiane Silvia
2 Martino, Josť Mario De
Affiliation1 State University of Campinas
2 State University of Campinas
EditorPapa, Jo„o Paulo
Sander, Pedro Vieira
Marroquim, Ricardo Guerra
Farrell, Ryan
e-Mail Addresstatiane.leite@gmail.com
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador
DateAug. 26-29, 2015
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2015-06-19 23:17:15 :: tatiane.leite@gmail.com -> administrator ::
2020-02-19 02:14:04 :: administrator -> :: 2015
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsfacial attractiveness
facial geometry
skin texture
machine learning
AbstractAdvertising images increasingly require attractive faces to attract the publics attention. Several studies have been conducted to enhance facial attractiveness in images. While some researchers suggest changes in geometrical shape, others advocate modifying the appearance of the facial skin; however, there have been few attempts to explore the possibility of combining both techniques. This paper sets out a novel method of doing this: facial geometry and skin texture modifications. Our method, which is based on supervised machine learning techniques, is able to improve the attractiveness of faces in images while preserving the original features of the picture. We also demonstrate the effectiveness of this combination by carrying out two different evaluations. Accordingly, we analyze the significance of each change that is designed to improve attractiveness by comparing the original image with a) the image in which only the facial geometry has been modified, b) the image in which only the texture skin has been modified and finally c) the image with both modifications. Our results reveal that the combination of geometric and skin texture modifications results in the most significant enhancement. It also demonstrates that modifications to the skin texture can be regarded as more important to obtain an attractive face than changes to the facial geometry. Additionally, evaluations are provided to quantify the gain in facial attractiveness and it should be pointed out that our method is the first to employ these, since there are no references to such tests in the literature.
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Languageen
Target FileImproving_the_attractiveness_of_faces_in_images.pdf
User Grouptatiane.leite@gmail.com
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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