Abstract
Facial trait judgments are an important information cue for people. Recent works in the Psychology field have stated the basis of face evaluation, defining a set of traits that we evaluate from faces (e.g. dominance, trustworthiness, aggressiveness, attractiveness, threatening or intelligence among others). We rapidly infer information from others faces, usually after a short period of time (< 1000ms) we perceive a certain degree of dominance or trustworthiness of another person from the face. Although these perceptions are not necessarily accurate, they influence many important social outcomes (such as the results of the elections or the court decisions). This topic has also attracted the attention of Computer Vision scientists, and recently a computational model to automatically predict trait evaluations from faces has been proposed. These systems try to mimic the human perception by means of applying machine learning classifiers to a set of labeled data. In this paper we perform an experimental study on the specific facial features that trigger the social inferences. Using previous results from the literature, we propose to use simple similarity maps to evaluate which regions of the face influence the most the trait inferences. The correlation analysis is performed using only appearance, and the results from the experiments suggest that each trait is correlated with specific facial characteristics.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Zebrowitz, L.: Reading faces: Window to the soul? Westview Press (1997)
Montepare, J., Zebrowitz, L.: Person perception comes of age: The salience and significance of age in social judgments. Advances in Experimental Social Psychology 30, 93–161 (1998)
Eagly, A., Ashmore, R., Makhijani, M., Longo, L.: What is beautiful is good, but: A meta-analytic review of research on the physical attractiveness stereotype. Psychological Bulletin; Psychological Bulletin 110(1), 109 (1991)
Ballew, C., Todorov, A.: Predicting political elections from rapid and unreflective face judgments. Proceedings of the National Academy of Sciences 104(46), 17948 (2007)
Little, A., Burriss, R., Jones, B., Roberts, S.: Facial appearance affects voting decisions. Evolution and Human Behavior 28(1), 18–27 (2007)
Blair, I., Judd, C., Chapleau, K.: The influence of afrocentric facial features in criminal sentencing. Psychological Science 15(10), 674 (2004)
Willis, J., Todorov, A.: First impressions making up your mind after a 100-ms exposure to a face. Psychological Science 17(7), 592–598 (2006)
Oosterhof, N., Todorov, A.: The functional basis of face evaluation. Proceedings of the National Academy of Sciences 105(32), 11087 (2008)
Todorov, A., Said, C., Engell, A., Oosterhof, N.: Understanding evaluation of faces on social dimensions. Trends in Cognitive Sciences 12(12), 455–460 (2008)
Phelps, E.A., LeDoux, J.E.: Contributions of the amygdala to emotion processing: from animal models to human behavior. Neuron 48(2), 175–187 (2005)
Adolphs, R., Tranel, D., Damasio, A., et al.: The human amygdala in social judgment. Nature, 470–473 (1998)
Rojas, Q., Masip, D., Todorov, A., Vitria, J., et al.: Automatic point-based facial trait judgments evaluation. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2715–2720. IEEE (2010)
Rojas, M., Masip, D., Todorov, A., Vitria, J.: Automatic prediction of facial trait judgments: Appearance vs. structural models. PloS one 6(8), e23323 (2011)
Lundqvist, D., Flykt, A., Ohman, A.: Karolinska Directed Emotional Faces: Database of standardized facial images. Psychology Section, Department of Clinical Neuroscience, Karolinska Hospital, S-171 76 Stockholm, Sweden (1998)
Torralba, A.: Contextual priming for object detection. International Journal of Computer Vision 53(2), 169–191 (2003)
Torralba, A.: Modeling global scene factors in attention. JOSA A 20(7), 1407–1418 (2003)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998)
Simoncelli, E., Freeman, W.: The steerable pyramid: A flexible architecture for multi-scale derivative computation. In: Proceedings of the International Conference on Image Processing, vol. 3, pp. 444–447. IEEE (1995)
Schyns, P., Oliva, A.: Flexible, diagnosticity-driven, rather than fixed, perceptually determined scale selection in scene and face recognition. Perception 26, 1027–1038 (1997)
Oliva, A., Schyns, P.: Coarse blobs or fine edges? evidence that information diagnosticity changes the perception of complex visual stimuli. Cognitive Psychology 34, 72–107 (1997)
Keil, M.S., Lapedriza, A., Masip, D., Vitria, J.: Preferred spatial frequencies for human face processing are associated with optimal class discrimination in the machine. PloS one 3(7), e2590 (2008)
Rayner, K.: Eye movements in reading and information processing: 20 years of research. Psychological Bulletin 124(3), 372 (1998)
Rao, R., Zelinsky, G., Hayhoe, M., Ballard, D.: Eye movements in iconic visual search. Vision Research 42(11), 1447–1463 (2002)
Henderson, J., Pollatsek, A., Rayner, K.: Covert visual attention and extrafoveal information use during object identification. Attention, Perception, & Psychophysics 45(3), 196–208 (1989)
Kowler, E., Anderson, E., Dosher, B., Blaser, E.: The role of attention in the programming of saccades. Vision Research 35(13), 1897–1916 (1995)
Henderson, J., McClure, K., Pierce, S., Schrock, G.: Object identification without foveal vision: Evidence from an artificial scotoma paradigm. Attention, Perception, & Psychophysics 59(3), 323–346 (1997)
Torralba, A., Oliva, A., Castelhano, M.S., Henderson, J.M.: Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search. Psychological Review 113(4), 766 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Masip Rodo, D., Todorov, A., Vitrià Marca, J. (2012). The Role of Facial Regions in Evaluating Social Dimensions. In: Fusiello, A., Murino, V., Cucchiara, R. (eds) Computer Vision – ECCV 2012. Workshops and Demonstrations. ECCV 2012. Lecture Notes in Computer Science, vol 7584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33868-7_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-33868-7_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33867-0
Online ISBN: 978-3-642-33868-7
eBook Packages: Computer ScienceComputer Science (R0)