Evolving Figurative Images Using Expression-Based Evolutionary Art

Aus de_evolutionary_art_org
Wechseln zu: Navigation, Suche


Joao Correia, Penousal Machado, Juan Romero, and Adrián Carballal: Evolving Figurative Images Using Expression-Based Evolutionary Art. In: Proceedings of the fourth International Conference on Computational Creativity (ICCC) Computational Creativity 2013 ICCC 2013, 2013, pp. 24-31.



The combination of a classifier system with an evolutionary image generation engine is explored. The framework is com- posed of an object detector and a general purpose, expression- based, genetic programming engine. Several object detec- tors are instantiated to detect faces, lips, breasts and leaves. The experimental results show the ability of the system to evolve images that are classified as the corresponding objects. A subjective analysis also reveals the unexpected nature and artistic potential of the evolved images.

Extended Abstract


author = {Joao Correia, Penousal Machado, Juan Romero, and Adrián Carballal},
title = {Evolving Figurative Images Using Expression-Based Evolutionary Art},
editor = {Simon Colton, Dan Ventura, Nada Lavrač, Michael Cook},
booktitle = {Proceedings of the Fourth International Conference on Computational Creativity},
series = {ICCC2013},
year = {2013},
month = {Jun},
location = {Sydney, New South Wales, Australia},
pages = {24-31},
url = {http://fmachado.dei.uc.pt/wp-content/papercite-data/pdf/cmrc13b.pdf, http://de.evo-art.org/index.php?title=Evolving_Figurative_Images_Using_Expression-Based_Evolutionary_Art },
publisher = {International Association for Computational Creativity},
keywords = {computational, creativity},

Used References

Baker, E. 1993. Evolving line drawings. Technical Report TR-21-93, Harvard University Center for Research in Com- puting Technology.

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

DiPaola, S. R., and Gabora, L. 2009. Incorporating char- acteristics of human creativity into an evolutionary art al- gorithm. Genetic Programming and Evolvable Machines 10(2):97–110.

Freund, Y., and Schapire, R. E. 1995. A decision-theoretic generalization of on-line learning and an application to boosting. In Proceedings of the Second European Confer- ence on Computational Learning Theory, EuroCOLT ’95, 23–37. London, UK, UK: Springer-Verlag.

Frowd, C. D.; Hancock, P. J. B.; and Carson, D. 2004. EvoFIT: A holistic, evolutionary facial imaging technique for creating composites. ACM Transactions on Applied Per- ception 1(1):19–39.

Griffin, G.; Holub, A.; and Perona, P. 2007. Caltech-256 object category dataset. Technical Report 7694, California Institute of Technology.

Johnston, V. S., and Caldwell, C. 1997. Tracking a crimi- nal suspect through face space with a genetic algorithm. In B ̈ack, T.; Fogel, D. B.; and Michalewicz, Z., eds., Hand- book of Evolutionary Computation. Bristol, New York: In- stitute of Physics Publishing and Oxford University Press. G8.3:1–8.

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

Lienhart, R., and Maydt, J. 2002. An extended set of haar- like features for rapid object detection. In International Con- ference on Image Processing, volume 1, I–900 – I–903 vol.1. Lienhart, R.; Kuranov, E.; and Pisarevsky, V. 2003. Empir- ical analysis of detection cascades of boosted classifiers for rapid object detection. In DAGM 25th Pattern Recognition Symposium, 297–304.

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

Machado, P., and Romero, J. 2011. On evolutionary computer-generated art. The Evolutionary Review: Art, Sci- ence, Culture 2(1):156–170.

Machado, P.; Correia, J.; and Romero, J. 2012a. Expression- based evolution of faces. In Evolutionary and Biologically Inspired Music, Sound, Art and Design - First International Conference, EvoMUSART 2012, M ́alaga, Spain, April 11- 13, 2012. Proceedings, volume 7247 of Lecture Notes in Computer Science, 187–198. Springer.

Machado, P.; Correia, J.; and Romero, J. 2012b. Improv- ing face detection. In Moraglio, A.; Silva, S.; Krawiec, K.; Machado, P.; and Cotta, C., eds., Genetic Programming - 15th European Conference, EuroGP 2012, M ́alaga, Spain, April 11-13, 2012. Proceedings, volume 7244 of Lecture Notes in Computer Science, 73–84. Springer.

Machado, P.; Romero, J.; and Manaris, B. 2007. Exper- iments in computational aesthetics: An iterative approach to stylistic change in evolutionary art. In Romero, J., and Machado, P., eds., The Art of Artificial Evolution: A Hand- book on Evolutionary Art and Music. Springer Berlin Hei- delberg. 381–415.

McCormack, J. 2005. Open problems in evolutionary mu- sic and art. In Rothlauf, F.; Branke, J.; Cagnoni, S.; Corne, D. W.; Drechsler, R.; Jin, Y.; Machado, P.; Marchiori, E.; Romero, J.; Smith, G. D.; and Squillero, G., eds., EvoWork- shops, volume 3449 of Lecture Notes in Computer Science, 428–436. Springer.

McCormack, J. 2007. Facing the future: Evolutionary pos- sibilities for human-machine creativity. In Romero, J., and Machado, P., eds., The Art of Artificial Evolution: A Hand- book on Evolutionary Art and Music. Springer Berlin Hei- delberg. 417–451.

Nishio, K.; Murakami, M.; Mizutani, E.; and N., H. 1997. Fuzzy fitness assignment in an interactive genetic algorithm for a cartoon face search. In Sanchez, E.; Shibata, T.; and Zadeh, L. A., eds., Genetic Algorithms and Fuzzy Logic Sys- tems: Soft Computing Perspectives, volume 7. World Scien- tific.

Norton, D.; Darrell, H.; and Ventura, D. 2010. Establishing appreciation in a creative system. In Proceedings of the First International Conference Computational Creativity, 26–35. Papageorgiou, C. P.; Oren, M.; and Poggio, T. 1998. A gen- eral framework for object detection. In Sixth International Conference on Computer Vision, 555–562.

Romero, J.; Machado, P.; Santos, A.; and Cardoso, A. 2003. On the development of critics in evolutionary computation artists. In G ̈unther, R., et al., eds., Applications of Evolution- ary Computing, EvoWorkshops 2003: EvoBIO, EvoCOM- NET, EvoHOT, EvoIASP, EvoMUSART, EvoSTOC, volume 2611 of LNCS. Essex, UK: Springer.

Santana, M. C.; D ́eniz-Su ́arez, O.; Ant ́on-Canal ́ıs, L.; and Lorenzo-Navarro, J. 2008. Face and facial feature detec- tion evaluation - performance evaluation of public domain haar detectors for face and facial feature detection. In Ran- chordas, A., and Ara ́ujo, H., eds., VISAPP (2), 167–172. INSTICC - Institute for Systems and Technologies of Infor- mation, Control and Communication.

Saunders, R., and Gero, J. 2001. The digital clockwork muse: A computational model of aesthetic evolution. In Wiggins, G., ed., AISB’01 Symposium on Artificial Intelli- gence and Creativity in Arts and Science, 12–21.

Secretan, J.; Beato, N.; D’Ambrosio, D. B.; Rodriguez, A.; Campbell, A.; Folsom-Kovarik, J. T.; and Stanley, K. O. 2011. Picbreeder: A case study in collaborative evolution- ary exploration of design space. Evolutionary Computation 19(3):373–403.

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

Ventrella, J. 2010. Self portraits with mandelbrot genet- ics. In Proceedings of the 10th international conference on Smart graphics, SG’10, 273–276. Berlin, Heidelberg: Springer-Verlag.

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

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


Full Text


intern file

Sonstige Links