Automatically generating abstract paintings in Malevich Style

Tao, Wenyuan; Liu, Yaxuan; Zhang, Kang

doi:10.1109/icis.2014.6912134

Cited by 11 publications

(8 citation statements)

References 7 publications

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“…As mentioned earlier, the Pollock Style work was accepted by the Visual Computer Journal; 24 the Drawer Tree paper was presented at ACM SAC 2014, for which the acceptance rate was 23.2 percent; 22 and the Malevich Style and Diamond Tree papers were presented at ICIS 2014. 20,23 For unknown reasons, the 3D Hyperbolic and Broccoli Tree teams did not follow up with complete drafts for submission.…”

Section: Results and Follow-upmentioning

confidence: 99%

“…This work was also presented at ICIS 2014. 23 The Pollock team came up with a layered approach to model Jackson Pollock's paint dripping style. Having analyzed fractal-based algorithms and observed the details of Pollock's paintings, they designed a layered modeling approach that divides Pollock's artwork into four layers from the bottom up: background, irregular shape, line, and water drop.…”

Section: Individual Projects Contributionsmentioning

confidence: 99%

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Teaching Information Aesthetics as a Research Class in China

Zhang

Nguyễn

Meng

et al. 2015

IEEE Comput. Grap. Appl.

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R esearch has traditionally been conducted in one-to-one or one-to-few training or tutoring settings, similar to apprenticeships practiced in many other lines of work. Such a small-scale tutoring mode has been effective in producing great researchers, but it is extremely costly in terms of manpower utilization of experienced researchers and educators. Research-based instructional strategies (RBISs) have been applied to enhance student learning, typically in the STEM (science, technology, engineering, and mathematics) disciplines. Class time devoted to RBIS is limited, 1 however, and recent studies show that such classroom interactions and after-class discussions are still lacking. 2 Nevertheless, we believe that various RBISs could be utilized to teach students to conduct productive research through projects in a classroom setting.This article reports on our experiences while attempting to scale up the research training in a typical Chinese class. Kang Zhang and Quang Vinh Nguyen jointly ran a research class in the School of Computer Software at Tianjin University, China, in the spring semester of 2013, with 41 undergraduate and master's students. The course research topic, information aesthetics, covered information visualization and generative art. Seven teams were set up to conduct seven different projects within the topic, and several were able to produce research papers published or accepted by journals and conferences (four publications out of the seven team projects).As part of this process, we developed an innovative method for setting up project teams based on the strengths of individual team members. We also were able to instruct undergraduate students along with their graduate peers. The most important learning experiences in teaching this class were de-termining how to enable effective team work and maximize the students' research potential. We believe that our model is replicable for larger classes and equally applicable to other disciplines. Class Setup and RequirementsOur research class had a regular course weight of 32 hours and two credits across 16 weeks, a typical master's course weight. It was offered in 2013 to both rst-year master's students and third-year undergraduate students. The course was called "Visual Languages and Visualization," and it required full participation and attendance by the students, with a sign-up sheet.The class syllabus included the following description:This course is research-oriented and targets students who are interested in research using graphs as a means for communication and problem solving, to represent program executions, and networked information. Topics in visual languages and information visualization will be discussed.The desirable prior knowledge for the students included computer graphics, compilers, humancomputer interfaces, and UML. Students were required to read papers on information visualization published in several recent journal issues and conference proceedings:■

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Section: Results and Follow-upmentioning

confidence: 99%

Section: Individual Projects Contributionsmentioning

confidence: 99%

Teaching Information Aesthetics as a Research Class in China

Zhang

Nguyễn

Meng

et al. 2015

IEEE Comput. Grap. Appl.

Self Cite

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“…He used different types of basic supremacist elements, such as quads, ovals, crosses, triangles, circles, straight lines and semi-crescent shapes. As noted by Tao et al [55] in Fig. 17, his works are frequently colored boldly and opaque geometric figures above a white or light colored background.…”

Section: Style Analysismentioning

confidence: 91%

“…Tao et al [55] attempt to automatically generate Malevich style of abstract paintings. They first decide the color and decorations of the background, then prepare the basic components with complexities and flexibilities.…”

Section: Rule-based Modelingmentioning

confidence: 99%

Computational aesthetics and applications

Zhang

2018

Vis. Comput. Ind. Biomed. Art

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Computational aesthetics, which bridges science and art, is emerging as a new interdisciplinary field. This paper concentrates on two main aspects of computational aesthetics: aesthetic measurement and quantification, generative art, and then proposes a design generation framework. On aesthetic measurement and quantification, we review different types of features used in measurement, the currently used evaluation methods, and their applications. On generative art, we focus on both fractal art and abstract paintings modeled on well-known artists' styles. In general, computational aesthetics exploits computational methods for aesthetic expressions. In other words, it enables computer to appraise beauty and ugliness and also automatically generate aesthetic images. Computational aesthetics has been widely applied to many areas, such as photography, fine art, Chinese handwriting , web design, graphic design, and industrial design. We finally propose a design generation methodology, utilizing techniques from both aesthetic measurements and generative art.

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“…The famous artist of impressionism, Paul Gauguin, also believed that art is abstract. Some scholars have conducted simulation research on the abstract painting style characteristics of famous artists [22][23][24].…”

Section: Related Workmentioning

confidence: 99%

Computer-Generated Abstract Paintings Oriented by the Color Composition of Images

2017

Information

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Designers and artists often require reference images at authoring time. The emergence of computer technology has provided new conditions and possibilities for artistic creation and research. It has also expanded the forms of artistic expression and attracted many artists, designers and computer experts to explore different artistic directions and collaborate with one another. In this paper, we present an efficient k-means-based method to segment the colors of an original picture to analyze the composition ratio of the color information and calculate individual color areas that are associated with their sizes. This information is transformed into regular geometries to reconstruct the colors of the picture to generate abstract images. Furthermore, we designed an application system using the proposed method and generated many works; some artists and designers have used it as an auxiliary tool for art and design creation. The experimental results of datasets demonstrate the effectiveness of our method and can give us inspiration for our work.

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Automatically generating abstract paintings in Malevich Style

Cited by 11 publications

References 7 publications

Teaching Information Aesthetics as a Research Class in China

Teaching Information Aesthetics as a Research Class in China

Computational aesthetics and applications

Computer-Generated Abstract Paintings Oriented by the Color Composition of Images

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