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Expression-Based Evolution of Faces

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7247)

Abstract

The combination of a classifier system with an evolutionary image generation engine is explored. The framework is instantiated using an off-the-shelf face detection system and a general purpose, expression-based, genetic programming engine. By default, the classifier returns a binary output, which is inadequate to guide evolution. By retrieving information provided by intermediate results of the classification task, it became possible to develop a suitable fitness function. The experimental results show the ability of the system to evolve images that are classified as faces. A subjective analysis also reveals the unexpected nature and artistic potential of the evolved images.

Keywords

  • Evolutionary Art
  • Automatic Fitness Assignment
  • Face Detection

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  • DOI: 10.1007/978-3-642-29142-5_17
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References

  1. Baker, E.: Evolving line drawings. Technical Report TR-21-93, Harvard University Center for Research in Computing Technology (1993)

    Google Scholar 

  2. Baluja, S., Pomerlau, D., Todd, J.: Towards automated artificial evolution for computer-generated images. Connection Science 6(2), 325–354 (1994)

    CrossRef  Google Scholar 

  3. DiPaola, S.R., Gabora, L.: Incorporating characteristics of human creativity into an evolutionary art algorithm. Genetic Programming and Evolvable Machines 10(2), 97–110 (2009)

    CrossRef  Google Scholar 

  4. Freund, Y., Schapire, R.E.: A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting (1995)

    Google Scholar 

  5. Frowd, C., Hancock, P.: Evolving human faces. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 189–210. Springer, Heidelberg (2007)

    Google Scholar 

  6. Johnston, V.S., Caldwell, C.: Tracking a criminal suspect through face space with a genetic algorithm. In: Bäck, T., Fogel, D.B., Michalewicz, Z. (eds.) Handbook of Evolutionary Computation, pp. G8.3:1–G8.3:8. Institute of Physics Publishing and Oxford University Press, Bristol (1997)

    Google Scholar 

  7. Lewis, M.: Evolutionary visual art and design. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 3–37. Springer, Heidelberg (2007)

    Google Scholar 

  8. Lienhart, R., Maydt, J.: An Extended Set of Haar-Like Features for Rapid Object Detection. In: IEEE ICIP 2002, pp. 900–903 (2002)

    Google Scholar 

  9. Machado, P., Cardoso, A.: All the truth about NEvAr. Applied Intelligence, Special Issue on Creative Systems 16(2), 101–119 (2002)

    MATH  Google Scholar 

  10. Machado, P., Romero, J., Manaris, B.: Experiments in computational aesthetics: An iterative approach to stylistic change in evolutionary art. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 381–415. Springer, Heidelberg (2007)

    Google Scholar 

  11. McCormack, J.: Facing the future: Evolutionary possibilities for human-machine creativity. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 417–451. Springer, Heidelberg (2007)

    Google Scholar 

  12. Nishio, K., et al.: Fuzzy fitness assignment in an interactive genetic algorithm for a cartoon face search. In: Sanchez, E., Shibata, T., Zadeh, L.A. (eds.) Genetic Algorithms and Fuzzy Logic Systems: Soft Computing Perspectives, vol. 7. World Scientific (1997)

    Google Scholar 

  13. Papageorgiou, C.P., Oren, M., Poggio, T.: A general framework for object detection. In: Sixth International Conference on Computer Vision, pp. 555–562 (January 1998)

    Google Scholar 

  14. Romero, J., Machado, P., Santos, A., Cardoso, A.: On the Development of Critics in Evolutionary Computation Artists. In: Raidl, G.R., Cagnoni, S., Cardalda, J.J.R., Corne, D.W., Gottlieb, J., Guillot, A., Hart, E., Johnson, C.G., Marchiori, E., Meyer, J.-A., Middendorf, M. (eds.) EvoWorkshops 2003. LNCS, vol. 2611, pp. 559–569. Springer, Heidelberg (2003)

    CrossRef  Google Scholar 

  15. Saunders, R., Gero, J.: The digital clockwork muse: A computational model of aesthetic evolution. In: Wiggins, G. (ed.) AISB 2001 Symposium on Artificial Intelligence and Creativity in Arts and Science, York, UK, pp. 12–21 (2001)

    Google Scholar 

  16. Sims, K.: Artificial evolution for computer graphics. ACM Computer Graphics 25, 319–328 (1991)

    CrossRef  Google Scholar 

  17. Spector, L., Alpern, A.: Criticism, culture, and the automatic generation of artworks. In: Proceedings of Twelfth National Conference on Artificial Intelligence, pp. 3–8. AAAI Press/MIT Press, Seattle, Washington, USA (1994)

    Google Scholar 

  18. Teller, A., Veloso, M.: Algorithm evolution for face recognition: what makes a picture difficult. In: IEEE International Conference on Evolutionary Computation (1995)

    Google Scholar 

  19. Ventrella, J.: Self Portraits with Mandelbrot Genetics. In: Taylor, R., Boulanger, P., Krüger, A., Olivier, P. (eds.) SG 2010. LNCS, vol. 6133, pp. 273–276. Springer, Heidelberg (2010), http://dl.acm.org/citation.cfm?id=1894345.1894382

    CrossRef  Google Scholar 

  20. Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, p. 511 (2001)

    Google Scholar 

  21. World, L.: Aesthetic selection: The evolutionary art of steven Rooke. IEEE Computer Graphics and Applications 16(1) (1996)

    Google Scholar 

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Machado, P., Correia, J., Romero, J. (2012). Expression-Based Evolution of Faces. In: Machado, P., Romero, J., Carballal, A. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2012. Lecture Notes in Computer Science, vol 7247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29142-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-29142-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29141-8

  • Online ISBN: 978-3-642-29142-5

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