IDEAS home Printed from https://ideas.repec.org/a/hin/complx/9270152.html
   My bibliography  Save this article

Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces

Author

Listed:
  • Felix Fuentes-Hurtado
  • Jose A. Diego-Mas
  • Valery Naranjo
  • Mariano Alcañiz

Abstract

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.

Suggested Citation

  • Felix Fuentes-Hurtado & Jose A. Diego-Mas & Valery Naranjo & Mariano Alcañiz, 2018. "Evolutionary Computation for Modelling Social Traits in Realistic Looking Synthetic Faces," Complexity, Hindawi, vol. 2018, pages 1-16, October.
    • Handle: RePEc:hin:complx:9270152
    DOI: 10.1155/2018/9270152
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/9270152.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/9270152.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/9270152?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mario Rojas Q. & David Masip & Alexander Todorov & Jordi Vitria, 2011. "Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-12, August.
    2. Matthias S Keil, 2009. "“I Look in Your Eyes, Honey”: Internal Face Features Induce Spatial Frequency Preference for Human Face Processing," PLOS Computational Biology, Public Library of Science, vol. 5(3), pages 1-13, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David Masip & Michael S North & Alexander Todorov & Daniel N Osherson, 2014. "Automated Prediction of Preferences Using Facial Expressions," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-5, February.
    2. L Jack Rhodes & Matthew Ríos & Jacob Williams & Gonzalo Quiñones & Prahalada K Rao & Vladimir Miskovic, 2019. "The role of low-level image features in the affective categorization of rapidly presented scenes," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-17, May.
    3. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).
    4. Thomas Brudermann & Gregory Bartel & Thomas Fenzl & Sebastian Seebauer, 2015. "Eyes on social norms: A field study on an honor system for newspaper sale," Theory and Decision, Springer, vol. 79(2), pages 285-306, September.
    5. Christianne Jacobs & Kirsten Petras & Pieter Moors & Valerie Goffaux, 2020. "Contrast versus identity encoding in the face image follow distinct orientation selectivity profiles," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-22, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:9270152. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.