ICONATE : Automatic Compound Icon Generation and Ideation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Author(s)

  • Nam Wook Kim
  • Laura Mariah Herman
  • Hanspeter Pfister
  • Jose Echevarria
  • Zoya Bylinskii

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationCHI‘20
Subtitle of host publicationProceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Number of pages13
ISBN (Electronic)978-1-4503-6708-0
Publication statusPublished - Apr 2020

Conference

Title2020 CHI Conference on Human Factors in Computing Systems, CHI 2020
LocationHawaii Convention Center
PlaceUnited States
CityHonolulu
Period25 - 30 April 2020

Abstract

Compound icons are prevalent on signs, webpages, and infographics, effectively conveying complex and abstract concepts, such as "no smoking" and "health insurance", with simple graphical representations. However, designing such icons requires experience and creativity, in order to efficiently navigate the semantics, space, and style features of icons. In this paper, we aim to automate the process of generating icons given compound concepts, to facilitate rapid compound icon creation and ideation. Informed by ethnographic interviews with professional icon designers, we have developed ICONATE, a novel system that automatically generates compound icons based on textual queries and allows users to explore and customize the generated icons. At the core of ICONATE is a computational pipeline that automatically finds commonly used icons for sub-concepts and arranges them according to inferred conventions. To enable the pipeline, we collected a new dataset, Compicon1k, consisting of 1000 compound icons annotated with semantic labels (i.e., concepts). Through user studies, we have demonstrated that our tool is able to automate or accelerate the compound icon design process for both novices and professionals.

Research Area(s)

  • Compound Icon, Ideogram, Pictogram, Icon Design, Graphic Design, Design Tools

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

ICONATE : Automatic Compound Icon Generation and Ideation. / Zhao, Nanxuan; Kim, Nam Wook; Herman, Laura Mariah; Pfister, Hanspeter; Lau, Rynson W.H.; Echevarria, Jose; Bylinskii, Zoya.

CHI‘20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2020. 491.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)