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.
Original language | English |
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Pages (from-to) | 968-978 |
Number of pages | 11 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 5308 |
Issue number | PART 2 |
DOIs | |
Publication status | Published - 2004 |
Externally published | Yes |
Event | Visual Communications and Image Processing 2004 - San Jose, CA, United States Duration: 20 Jan 2004 → 22 Jan 2004 |
Keywords
- Facial beauty classification
- Facial features
- Golden proportion
- Performance evaluation
- Supervised learning