Abstract
This paper investigates the feasibility of evolutionary search techniques as a mechanism for interactively exploring the design space of 2D painterly renderings. Although a growing body of painterly rendering literature exists, the large number of low-level configurable parameters that feature in contemporary algorithms can be counter-intuitive for non-expert users to set. In this paper we first describe a multi-resolution painting algorithm capable of transforming photographs into paintings at interactive speeds. We then present a supervised evolutionary search process in which the user scores paintings on their aesthetics to guide the specification of their desired painterly rendering. Using our system, non-expert users are able to produce their desired aesthetic in approximately 20 mouse clicks — around half an order of magnitude faster than manual specification of individual rendering parameters by trial and error.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Curtis, C., Anderson, S., Seims, J., Fleischer, K., Salesin, D.H.: Computergenerated watercolor. In: Proc. ACM SIGGRAPH, pp. 421–430 (1997)
Litwinowicz, P.: Processing images and video for an impressionist effect. In: Proc. ACM SIGGRAPH, Los Angeles, USA, pp. 407–414 (1997)
Hertzmann, A.: Painterly rendering with curved brush strokes of multiple sizes. In: Proc. ACM SIGGRAPH, pp. 453–460 (1998)
Shiraishi, M., Yamaguchi, Y.: An algorithm for automatic painterly rendering based on local image approximation. In: Proc. ACM NPAR Sympos., pp. 53–58 (2000)
Gooch, B., Coombe, G., Shirley, P.: Artistic vision: Painterly rendering using computer vision techniques. In: Proc. ACM NPAR Sympos., pp. 83–90 (2002)
Hays, J., Essa, I.: Image and video based painterly animation. In: Proc. ACM NPAR Sympos., pp. 113–120 (2004)
Collomosse, J.P., Hall, P.M.: Genetic paint: A search for salient paintings. In: Rothlauf, F., Branke, J., Cagnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romero, J., Smith, G.D., Squillero, G. (eds.) EvoWorkshops 2005. LNCS, vol. 3449, pp. 437–447. Springer, Heidelberg (2005)
Sims, K.: Artificial evolution for computer graphics. In: Proc. ACM SIGGRAPH, vol. 25, pp. 319–328 (1991)
Ebner, M., Reinhardt, M., Albert, J.: Evolution of vertex and pixel shaders. In: Keijzer, M., Tettamanzi, A.G.B., Collet, P., van Hemert, J., Tomassini, M. (eds.) EuroGP 2005. LNCS, vol. 3447, pp. 261–270. Springer, Heidelberg (2005)
Draves, S.: The electric sheep screen-saver: A case study in aesthetic evolution. In: Rothlauf, F., Branke, J., Cagnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romero, J., Smith, G.D., Squillero, G. (eds.) EvoWorkshops 2005. LNCS, vol. 3449, pp. 458–467. Springer, Heidelberg (2005)
Russell, J.A.: Reading emotion from and into faces: Resurrecting a dimensionalcontextual perspective. In: Russel, J.A., Fernández-Dols, J.M. (eds.) The Psychology of Facial Expression, pp. 295–320. Cambridge University Press, Cambridge (1997)
Shugrina, M., Betke, M., Collomosse, J.P.: Empathic painting: Interactive stylization using observed emotional state. In: Proc. ACM NPAR Sympos. (2006)
Haeberli, P.: Paint by numbers: abstract image representations. In: Proc. ACM SIGGRAPH, vol. 4, pp. 207–214 (1990)
Hertzmann, A.: Paint by relaxation. In: Proc. Computer Graphics Intl. (CGI), pp. 47–54 (2001)
Treavett, S., Chen, M.: Statistical techniques for the automated synthesis of nonphotorealistic images. In: Proc. 15th Eurographics UK Conference, pp. 201–210 (1997)
DeCarlo, D., Santella, A.: Abstracted painterly renderings using eye-tracking data. In: Proc. ACM SIGGRAPH, pp. 769–776 (2002)
Santella, A., DeCarlo, D.: Visual interest and NPR: an evaluation and manifesto. In: Proc. ACM NPAR Sympos., pp. 71–78 (2004)
Christoudias, C., Georgescu, B., Meer, P.: Synergism in low level vision. In: 16th Intl. Conf. on Pattern Recognition, vol. 4, pp. 150–155 (2002)
Kolliopoulos, A.: Image segmentation for stylized non-photorealistic rendering and animation. Master’s thesis, Univ. Toronto (2005)
Wright, B., Rainwater, L.: The meaning of colour. Journal of General Psychology 67 (1962)
Mahnke, F.: Color, Environment, and Human Response. Van Nostrand Reinhold (1996)
de Jong, K.: Learning with genetic algorithms. Machine Learning 3, 121–138 (1988)
Holland, J.: Adaptation in Natural and Artificial Systems, 1st edn. Univ. Michigan Press (1975) ISBN: 0-472-08460-7
Hertzmann, A., Perlin, K.: Painterly rendering for video and interaction. In: Proc. ACM NPAR Sympos., pp. 7–12 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Collomosse, J.P. (2006). Supervised Genetic Search for Parameter Selection in Painterly Rendering. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_57
Download citation
DOI: https://doi.org/10.1007/11732242_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33237-4
Online ISBN: 978-3-540-33238-1
eBook Packages: Computer ScienceComputer Science (R0)