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Proceedings Paper

Automated classification of female facial beauty by image analysis and supervised learning
Author(s): Hatice Gunes; Massimo Piccardi; Tony Jan
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Paper Abstract

The fact that perception of facial beauty may be a universal concept has long been debated amongst psychologists and anthropologists. In this paper, we performed experiments to evaluate the extent of beauty universality by asking a number of diverse human referees to grade a same collection of female facial images. Results obtained show that the different individuals gave similar votes, thus well supporting the concept of beauty universality. We then trained an automated classifier using the human votes as the ground truth and used it to classify an independent test set of facial images. The high accuracy achieved proves that this classifier can be used as a general, automated tool for objective classification of female facial beauty. Potential applications exist in the entertainment industry and plastic surgery.

Paper Details

Date Published: 18 January 2004
PDF: 11 pages
Proc. SPIE 5308, Visual Communications and Image Processing 2004, (18 January 2004); doi: 10.1117/12.526531
Show Author Affiliations
Hatice Gunes, Univ. of Technology/Sydney (Australia)
Massimo Piccardi, Univ. of Technology/Sydney (Australia)
Tony Jan, Univ. of Technology/Sydney (Australia)

Published in SPIE Proceedings Vol. 5308:
Visual Communications and Image Processing 2004
Sethuraman Panchanathan; Bhaskaran Vasudev, Editor(s)

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