Computational aesthetics and applications

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.

A review of design intelligence:progress,problems,and challenges

Design intelligence is an important branch of artificial intelligence(AI),focusing on the intelligent models and algorithms in creativity and design.In the context of AI 2.0,studies on design intelligence have developed rapidly.We summarize mainly the current emerging framework of design intelligence and review the state-of-the-art techniques of related topics,including user needs analysis,ideation,content generation,and design evaluation.Specifically,the models and methods of intelligence-generated content are reviewed in detail.Finally,we discuss some open problems and challenges for future research in design intelligence.