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International Conference on Intelligent Virtual Agents

IVA 2017: Intelligent Virtual Agents pp 301–314Cite as

Generation of Virtual Characters from Personality Traits

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10498))

Abstract

We present a method to generate a virtual character whose physical attributes reflect public opinion of a given personality profile. An initial reverse correlation experiment trains a model which explains the perception of personality traits from physical attributes. The reverse model, solved using linear programming, allows for the real-time generation of virtual characters from an input personality. The method has been applied on three personality traits (dominance, trustworthiness, and agreeableness) and 14 physical attributes and verified through both an analytic test and a subjective study.

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References

  1. Ames, D.R., Bianchi, E.C.: The agreeableness asymmetry in first impressions: Perceivers’ impulse to (mis)judge agreeableness and how it is moderated by power. Personality and Social Psychology Bulletin 34(12), 1719–1736 (2008)

    Article  Google Scholar 

  2. Bradley, R.A., Terry, M.E.: Rank analysis of incomplete block designs. Biometrika 39, 324–335 (1952)

    MathSciNet  MATH  Google Scholar 

  3. Cassell, J.: Social practice: becoming enculturated in human-computer interaction. In: Stephanidis, C. (ed.) UAHCI 2009. LNCS, vol. 5616, pp. 303–313. Springer, Heidelberg (2009). doi:10.1007/978-3-642-02713-0_32

    Chapter  Google Scholar 

  4. Dotsch, R., Todorov, A.: Reverse correlating social face perception. Social Psychological and Personality Science 3(5), 562–571 (2012)

    Article  Google Scholar 

  5. Durupinar, F., Kapadia, M., Deutsch, S., Neff, M., Badler, N.I.: PERFORM: Perceptual approach for adding OCEAN personality to human motion using laban movement analysis. ACM Transactions on Graphics 36(1), 1–16 (2016)

    Article  Google Scholar 

  6. Hatzinger, R., Dittrich, R.: prefmod: an R package for modeling preferences based on paired comparisons, rankings, or ratings. Journal of Statistical Software 48(10), 1–31 (2012)

    Article  Google Scholar 

  7. Loyall, A.B.: Believable agents: building interactive personalities. PhD dissertation, Carnegie Mellon University, Pittsburgh (1997)

    Google Scholar 

  8. Mangini, M.C., Biederman, I.: Making the ineffable explicit: estimating the information employed for face classifications. Cognitive Science 28(2), 209–226 (2004)

    Article  Google Scholar 

  9. Mansour, S., El-Said, M., Rude-Parkins, C., Nandigam, J.: The interactive effect of avatar visual fidelity and behavioral fidelity in the collaborative virtual reality environment on the perception of social interaction. In: Proceedings of the 10th International Conference on Communications, pp. 387–395. WSEAS (2006)

    Google Scholar 

  10. Martinez, H., Yannakakis, G., Hallam, J.: Don’t classify ratings of affect; rank them!. IEEE Transactions on Affective Computing 5(3), 314–326 (2014)

    Article  Google Scholar 

  11. McCrae, R.R., John, O.P.: An introduction to the five-factor model and its applications. Journal of Personality 60(2), 175–215 (1992)

    Article  Google Scholar 

  12. Oosterhof, N.N., Todorov, A.: The functional basis of face evaluation. Proceedings of the National Academy of Sciences 105(32), 11087–11092 (2008)

    Article  Google Scholar 

  13. Streuber, S., Quiros-Ramirez, M.A., Hill, M.Q., Hahn, C.A., Zuffi, S., O’Toole, A., Black, M.J.: Body Talk: Crowdshaping realistic 3d avatars with words. ACM Trans. Graph. 35(4), 54:1–54:14 (2016)

    Article  Google Scholar 

  14. Toscano, H., Schubert, T., Sell, A.N.: Judgments of dominance from the face track physical strength. Evolutionary Psychology 12(1), 1–18 (2014)

    Article  Google Scholar 

  15. Vernon, R.J.W., Sutherland, C.A.M., Young, A.W., Hartley, T.: Modeling first impressions from highly variable facial images. Proceedings of the National Academy of Sciences 111(32), E3353–E3361 (2014)

    Article  Google Scholar 

  16. 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)

    Article  Google Scholar 

  17. Windhager, S., Schaefer, K., Fink, B.: Geometric morphometrics of male facial shape in relation to physical strength and perceived attractiveness, dominance, and masculinity. American Journal of Human Biology 23(6), 805–814 (2011)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. DFKI-MMCI, SLSI group, Saarbrücken, Germany

    Fabrizio Nunnari & Alexis Heloir

  2. LAMIH UMR CNRS/UVHC 8201, Valenciennes, France

    Alexis Heloir

Authors
  1. Fabrizio Nunnari
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  2. Alexis Heloir
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Corresponding author

Correspondence to Fabrizio Nunnari .

Editor information

Editors and Affiliations

  1. KTH Royal Institute of Technology, Stockholm, Sweden

    Jonas Beskow

  2. KTH Royal Institute of Technology, Stockholm, Sweden

    Christopher Peters

  3. Uppsala University, Uppsala, Sweden

    Ginevra Castellano

  4. Trinity College, Dublin, Ireland

    Carol O'Sullivan

  5. KTH Royal Institute of Technology, Stockholm, Sweden

    Iolanda Leite

  6. University of Bielefeld, Bielefeld, Germany

    Stefan Kopp

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© 2017 Springer International Publishing AG

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Nunnari, F., Heloir, A. (2017). Generation of Virtual Characters from Personality Traits. In: Beskow, J., Peters, C., Castellano, G., O'Sullivan, C., Leite, I., Kopp, S. (eds) Intelligent Virtual Agents. IVA 2017. Lecture Notes in Computer Science(), vol 10498. Springer, Cham. https://doi.org/10.1007/978-3-319-67401-8_39

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  • DOI: https://doi.org/10.1007/978-3-319-67401-8_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67400-1

  • Online ISBN: 978-3-319-67401-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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