Computational aesthetics and applications

• Main Authors: Yihang Bo, Jinhui Yu, Kang Zhang
• Format: Article
• Language: English
• Published: SpringerOpen 2018-09-01
• Series: Visual Computing for Industry, Biomedicine, and Art
• Subjects: Computational aesthetics; Aesthetic measurement; Generative art; Fractal art; Abstract painting
• Online Access: http://link.springer.com/article/10.1186/s42492-018-0006-1

Abstract 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 hand-writing, web design, graphic design, and industrial design. We finally propose a design generation methodology, utilizing techniques from both aesthetic measurements and generative art.