Generation of Miro's Surrealism

In this paper, we present a programmed experiment and the results on automatic generation of Joan Miro style of surrealism. Combining the artist's aesthetic theory with the authors' own understanding, the paper analyzes the characteristics of Miro's work and proposes a process modeling approach that consists of four steps: structured drawing, adaptive coloring, space filling and noise injection. The generation process is described in details and sample generated images styled on Miro's paintings are also demonstrated and discussed. By extracting and coding pictorial elements in paintings of Miro, different styled images could be generated under different sets of parameters.

[1]  Leon A. Gatys,et al.  A Neural Algorithm of Artistic Style , 2015, ArXiv.

[2]  Paul Cézanne,et al.  Cezanne: Landscape into Art , 1996 .

[3]  Yvonne Neudorf,et al.  Cubism A History And An Analysis 1907 1914 , 2016 .

[4]  Richard P Taylor.  Order in Pollock's chaos. , 2002, Scientific American.

[5]  Joan L. Russell A. Kirsch,et al.  The Anatomy of Painting Style: Description with Computer Rules , 2017 .

[6]  Russell A. Hill,et al.  Evolutionary perspectives on sport and competition , 2011 .

[7]  Richard P. Taylor,et al.  Fractal analysis of Pollock's drip paintings , 1999, Nature.

[8]  Renee Riese Hubert.  Miro and Breton , 1964 .

[9]  Casey Reas,et al.  Processing: a programming handbook for visual designers and artists , 2007 .

[10]  Kang Zhang,et al.  Computer Graphics for Java Programmers , 2017, Springer International Publishing.

[11]  Kang Zhang,et al.  Generation of Kandinsky Art , 2016, Leonardo.

[12]  Paul Haeberli,et al.  Paint by numbers: abstract image representations , 1990, SIGGRAPH.

[13]  Greg Judelman,et al.  Aesthetics and inspiration for visualization design: bridging the gap between art and science , 2004, Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004..

[14]  A. Noll.  Human or Machine: A Subjective Comparison of Piet Mondrian’s “Composition with Lines” (1917) and a Computer-Generated Picture , 1966 .

[15]  Alex Danchev,et al.  Cezanne: A Life , 2012 .

[16]  Margit Rowell,et al.  Joan Miro Selected Writings and Interviews , 1987 .

[17]  T. Whitfield,et al.  Color psychology: a critical review. , 1990, Genetic, social, and general psychology monographs.

[18]  Henrik Jeldtoft Jensen.  Mathematics and painting , 2002 .

[19]  Kang Zhang,et al.  From Abstract Painting to Information Visualization , 2007, IEEE Computer Graphics and Applications.

[20]  David Jonas,et al.  The Construction of Jackson Pollock's Fractal Drip Paintings , 2002, Leonardo.

[21]  Kang Zhang,et al.  Computational Aesthetics: On the Complexity of Computer-Generated Paintings , 2012, Leonardo.

[22]  Emily Braun,et al.  Cubism : the Leonard A. Lauder collection , 2014 .

[23]  Kang Zhang,et al.  Automatically generating abstract paintings in Malevich Style , 2014, 2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS).

[24]  Griselda Pollock,et al.  Melancholia and Cézanne's Portraits: Faces Beyond the Mirror , 2008 .

[25]  Song-Chun Zhu,et al.  Sisley the abstract painter , 2010, NPAR.

[26]  Kang Zhang,et al.  Layered modeling and generation of Pollock’s drip style , 2015, The Visual Computer.

[27]  Ernest A. Edmonds,et al.  What is generative art? , 2009, Digit. Creativity.

[28]  Michael F. Barnsley,et al.  Fractals everywhere , 1988 .

[29]  Adérito Marcos.  Digital Art: When Artistic and Cultural Muse Merges with Computer Technology , 2007, IEEE Computer Graphics and Applications.