Situated color aesthetics by evolutionary computation

Michael S. Bittermann, Özer Ciftcioglu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In a previous publication by the same authors, a computational design system was described that identifies aesthetical color combinations. In that work the type of color aesthetics pursued was to be determined prior to the design representing a given design objective. Complementing the previous study, in this work, the type of color aesthetics that is most suitable for a given scene at hand is pursued taking into account the color and geometry of an existing situation. This is accomplished by bringing the parameter that characterizes the type of aesthetics into computational design, i.e. treating it as one of the components of the decision variable vector subject to identification by multi-objective evolutionary search. The parameter's influence on aesthetics is investigated theoretically, as well as by means of computer experiments. The contribution of the study to Architecture is provision of a firm base for some common architectural knowledge as to the color aesthetics of buildings. In particular light is shed on the aesthetical dependence of a building's color to the color of its environment.

Original languageEnglish
Title of host publication2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages936-943
Number of pages8
ISBN (Electronic)9781509046010
DOIs
Publication statusPublished - 5 Jul 2017
Externally publishedYes
Event2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Spain
Duration: 5 Jun 20178 Jun 2017

Publication series

Name2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings

Conference

Conference2017 IEEE Congress on Evolutionary Computation, CEC 2017
Country/TerritorySpain
CityDonostia-San Sebastian
Period5/06/178/06/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

  • Aesthetics
  • Architectural
  • Design
  • Fuzzy neural tree
  • Pareto optimal front
  • Visual perception

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