Automatic evaluation of facial attractiveness (CROSBI ID 581196)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Sutić, Davor ; Brešković, Ivan ; Huić, Rene ; Jukić, Ivan
engleski
Automatic evaluation of facial attractiveness
In this paper we present an approach of applying machine learning algorithms to the task of predicting human attractiveness. We have collected human beauty ratings of female facial images. We have chosen eigenfaces and ratio-based features as face representations. Along with k-nearest neighbors, we have used neural network and AdaBoost algorithms, which had not been used for this task before. Our analysis shows that machine learning algorithms have a preference towards facial symmetry, but also that a wider set of features needs to be included. We validate our results with a survey of four participants, which shows that facial attractiveness is a highly subjective judgement.
machine learning; face representations; neural network; AdaBoost algorithms; facial attractiveness
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Podaci o prilogu
1339-1342.
2010.
objavljeno
Podaci o matičnoj publikaciji
MIPRO, 2010 Proceedings of the 33rd International Convention Issue Date: 24-28 May 2010
Opatija: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO
978-1-4244-7763-0
Podaci o skupu
33 rd International Convention MIPRO
predavanje
24.05.2010-28.05.2010
Opatija, Hrvatska