NEURAL NETWORK COMPUTABILITY OF FACE-BASED ATTRACTIVENESS

Joshua Chauvin, Marcello Guarini, Christopher Abeare

Abstract

In this work we have explored facial attractiveness as well as sex classification through the application of feed-forward artificial neural network (ANN) models. Data was collected from participants to compile a face database that was later rated by human raters. The neural network analyzed facial images as pixel-data that was converted into vectors. Prediction was carried out by first training the neural network on a number of images (along with their respective attractiveness ratings) and then testing it on new stimuli in order to make generalizations. There was strong intraclass correlation (ICC) and agreement between the neural network outputs and the human raters on facial attractiveness. This project’s success provides novel evidence for the hypothesis that there are objective regularities in facial attractiveness. In addition, there is some indication that the confidence with which sex classification is performed is related to attractiveness. This paper corroborates the work of others that suggests facial attractiveness judgments can be learned by machines.

References

  1. Bronstad, P. M., Langlois, J. H., & Russell, R. (2008). Computational models of facial attractiveness judgments. Perception, 37(1), 126.
  2. Cheng, Y. D., O'Toole, A. J., & Abdi, H. (2001). Classifying adults' and children's faces by sex: Computational investigations of subcategorical feature encoding. Cognitive Science: A Multidisciplinary Journal, 25(5), 819-838.
  3. Cunningham, M. R., Roberts, A. R., Barbee, A. P., Druen, P. B., & Wu, C. H. (1995). Their ideas of beauty are, on the whole, the same as ours: Consistency and variability in the cross-cultural perception of female physical attractiveness. Journal of Personality and Social Psychology, 68(2), 261-279.
  4. Dailey, M. N., Cottrell, G. W., Padgett, C., & Adolphs, R. (2002). EMPATH: A neural network that categorizes facial expressions. Journal of Cognitive Neuroscience, 14(8), 1158-1173.
  5. DeSantis, A., & Kayson, W. A. (1997). Defendants' characteristics of attractiveness, race, and sex and sentencing decisions. Psychological Reports, 81(2), 679-683.
  6. Eisenthal, Y., Dror, G., & Ruppin, E. (2006). Facial attractiveness: Beauty and the machine. Neural Computation, 18(1), 119-142.
  7. Feingold, A. (1992). Gender differences in mate selection preferences: A test of the parental investment model. Psychological Bulletin, 112(1), 125-139.
  8. Fiske, S. T. (2001). Effects of power on bias: Power explains and maintains individual, group, and societal disparities. The use and abuse of power: Multiple perspectives on the causes of corruption, 181-193.
  9. Furl, N., Phillips, P. J., & O'Toole, A. J. (2002). Face recognition algorithms and the other-race effect: Computational mechanisms for a developmental contact hypothesis. Cognitive Science: A Multidisciplinary Journal, 26(6), 797-815.
  10. Grammer, K., & Thornhill, R. (1994). Human (Homo sapiens) facial attractiveness and sexual selection: The role of symmetry and averageness. Journal of Comparative Psychology, 108(3), 233-242.
  11. Highfield, R., Wiseman, R., & Jenkins, R. (2009). In your face. New Scientist, 201(2695), 28-32.
  12. John, O. P., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. Handbook of personality: Theory and research, 2, 102-138.
  13. Langlois, J. H., & Roggman, L. A. (1990). Attractive faces are only average. Psychological Science, 1(2), 115- 121.
  14. Locher, P., Unger, R., Sociedade, P., & Wahl, J. (1993). At first glance: Accessibility of the physical attractiveness stereotype. Sex Roles, 28(11), 729-743.
  15. Perrett, D. I., Lee, K. J., Penton-Voak, I., Rowland, D., Yoshikawa, S., Burt, D. M., et al. (2002). Effects of sexual dimorphism on facial attractiveness. Foundations in Social Neuroscience, 937.
  16. Rhodes, G., Sumich, A., & Byatt, G. (1999). Are average facial configurations attractive only because of their symmetry? Psychological Science, 10(1), 52-58.
  17. Romano, S. T., & Bordieri, J. E. (1989). Physical attractiveness stereotypes and students' perceptions of college professors. Psychological Reports, 64(3 Pt 2), 1099-1102.
  18. Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychol Bull, 86(2), 420-428.
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Paper Citation


in Harvard Style

Chauvin J., Guarini M. and Abeare C. (2009). NEURAL NETWORK COMPUTABILITY OF FACE-BASED ATTRACTIVENESS . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 473-479. DOI: 10.5220/0002322504730479


in Bibtex Style

@conference{icnc09,
author={Joshua Chauvin and Marcello Guarini and Christopher Abeare},
title={NEURAL NETWORK COMPUTABILITY OF FACE-BASED ATTRACTIVENESS},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)},
year={2009},
pages={473-479},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002322504730479},
isbn={978-989-674-014-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)
TI - NEURAL NETWORK COMPUTABILITY OF FACE-BASED ATTRACTIVENESS
SN - 978-989-674-014-6
AU - Chauvin J.
AU - Guarini M.
AU - Abeare C.
PY - 2009
SP - 473
EP - 479
DO - 10.5220/0002322504730479