@InProceedings{LeiteMart:2015:ImAtFa,
author = "Leite, Tatiane Silvia and Martino, Jos{\'e} Mario De",
affiliation = "{State University of Campinas} and {State University of
Campinas}",
title = "Improving the attractiveness of faces in images",
booktitle = "Proceedings...",
year = "2015",
editor = "Papa, Jo{\~a}o Paulo and Sander, Pedro Vieira and Marroquim,
Ricardo Guerra and Farrell, Ryan",
organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "facial attractiveness, facial geometry, skin texture, machine
learning.",
abstract = "Advertising 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.",
conference-location = "Salvador, BA, Brazil",
conference-year = "26-29 Aug. 2015",
doi = "10.1109/SIBGRAPI.2015.13",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2015.13",
language = "en",
ibi = "8JMKD3MGPBW34M/3JMPBEE",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3JMPBEE",
targetfile = "Improving_the_attractiveness_of_faces_in_images.pdf",
urlaccessdate = "2024, Apr. 27"
}