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
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baker, E.: Evolving line drawings. Technical Report TR-21-93, Harvard University Center for Research in Computing Technology (1993)
Baluja, S., Pomerlau, D., Todd, J.: Towards automated artificial evolution for computer-generated images. Connection Science 6(2), 325–354 (1994)
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)
Freund, Y., Schapire, R.E.: A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting (1995)
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)
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)
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)
Lienhart, R., Maydt, J.: An Extended Set of Haar-Like Features for Rapid Object Detection. In: IEEE ICIP 2002, pp. 900–903 (2002)
Machado, P., Cardoso, A.: All the truth about NEvAr. Applied Intelligence, Special Issue on Creative Systems 16(2), 101–119 (2002)
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)
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)
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)
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)
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)
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)
Sims, K.: Artificial evolution for computer graphics. ACM Computer Graphics 25, 319–328 (1991)
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)
Teller, A., Veloso, M.: Algorithm evolution for face recognition: what makes a picture difficult. In: IEEE International Conference on Evolutionary Computation (1995)
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
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)
World, L.: Aesthetic selection: The evolutionary art of steven Rooke. IEEE Computer Graphics and Applications 16(1) (1996)
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
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
Download citation
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
eBook Packages: Computer ScienceComputer Science (R0)