Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces

Human faces play a central role in our lives. Thanks to our behavioural capacity to perceive faces, how a face looks in a painting, a movie, or an advertisement can dramatically influence what we feel about them and what emotions are elicited. Facial information is processed by our brain in such a w...

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Main Authors: Felix Fuentes-Hurtado, Jose A. Diego-Mas, Valery Naranjo, Mariano Alcañiz
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/9270152
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author Felix Fuentes-Hurtado
Jose A. Diego-Mas
Valery Naranjo
Mariano Alcañiz
author_facet Felix Fuentes-Hurtado
Jose A. Diego-Mas
Valery Naranjo
Mariano Alcañiz
author_sort Felix Fuentes-Hurtado
collection DOAJ
description Human faces play a central role in our lives. Thanks to our behavioural capacity to perceive faces, how a face looks in a painting, a movie, or an advertisement can dramatically influence what we feel about them and what emotions are elicited. Facial information is processed by our brain in such a way that we immediately make judgements like attractiveness or masculinity or interpret personality traits or moods of other people. Due to the importance of appearance-driven judgements of faces, this has become a major focus not only for psychological research, but for neuroscientists, artists, engineers, and software developers. New technologies are now able to create realistic looking synthetic faces that are used in arts, online activities, advertisement, or movies. However, there is not a method to generate virtual faces that convey the desired sensations to the observers. In this work, we present a genetic algorithm based procedure to create realistic faces combining facial features in the adequate relative positions. A model of how observers will perceive a face based on its features’ appearances and relative positions was developed and used as the fitness function of the algorithm. The model is able to predict 15 facial social traits related to aesthetic, moods, and personality. The proposed procedure was validated comparing its results with the opinion of human observers. This procedure is useful not only for creating characters with artistic purposes, but also for online activities, advertising, surgery, or criminology.
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publishDate 2018-01-01
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spelling doaj-art-78281b97f2134bcc9b5f56f94b34e6912025-08-20T03:35:11ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/92701529270152Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic FacesFelix Fuentes-Hurtado0Jose A. Diego-Mas1Valery Naranjo2Mariano Alcañiz3i3B, Institute for Research and Innovation in Bioengineering, Universitat Politecnica de Valencia, 46022 Valencia, Spaini3B, Institute for Research and Innovation in Bioengineering, Universitat Politecnica de Valencia, 46022 Valencia, Spaini3B, Institute for Research and Innovation in Bioengineering, Universitat Politecnica de Valencia, 46022 Valencia, Spaini3B, Institute for Research and Innovation in Bioengineering, Universitat Politecnica de Valencia, 46022 Valencia, SpainHuman faces play a central role in our lives. Thanks to our behavioural capacity to perceive faces, how a face looks in a painting, a movie, or an advertisement can dramatically influence what we feel about them and what emotions are elicited. Facial information is processed by our brain in such a way that we immediately make judgements like attractiveness or masculinity or interpret personality traits or moods of other people. Due to the importance of appearance-driven judgements of faces, this has become a major focus not only for psychological research, but for neuroscientists, artists, engineers, and software developers. New technologies are now able to create realistic looking synthetic faces that are used in arts, online activities, advertisement, or movies. However, there is not a method to generate virtual faces that convey the desired sensations to the observers. In this work, we present a genetic algorithm based procedure to create realistic faces combining facial features in the adequate relative positions. A model of how observers will perceive a face based on its features’ appearances and relative positions was developed and used as the fitness function of the algorithm. The model is able to predict 15 facial social traits related to aesthetic, moods, and personality. The proposed procedure was validated comparing its results with the opinion of human observers. This procedure is useful not only for creating characters with artistic purposes, but also for online activities, advertising, surgery, or criminology.http://dx.doi.org/10.1155/2018/9270152
spellingShingle Felix Fuentes-Hurtado
Jose A. Diego-Mas
Valery Naranjo
Mariano Alcañiz
Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces
Complexity
title Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces
title_full Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces
title_fullStr Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces
title_full_unstemmed Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces
title_short Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces
title_sort evolutionary computation for modelling social traits in realistic looking synthetic faces
url http://dx.doi.org/10.1155/2018/9270152
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AT joseadiegomas evolutionarycomputationformodellingsocialtraitsinrealisticlookingsyntheticfaces
AT valerynaranjo evolutionarycomputationformodellingsocialtraitsinrealisticlookingsyntheticfaces
AT marianoalcaniz evolutionarycomputationformodellingsocialtraitsinrealisticlookingsyntheticfaces