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A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design

The nature of environment concept design is a visual-based issue, where designers need to find loads of visual stimuli to create the high-quality concept. This paper aims to introduce a novel AI-based method to automatically generate images as design inspiration for environment concept design. Throu...

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Detalles Bibliográficos
Autores principales: Duan, Yingjing, Zhang, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249455/
https://www.ncbi.nlm.nih.gov/pubmed/35785079
http://dx.doi.org/10.1155/2022/8015492
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author Duan, Yingjing
Zhang, Jie
author_facet Duan, Yingjing
Zhang, Jie
author_sort Duan, Yingjing
collection PubMed
description The nature of environment concept design is a visual-based issue, where designers need to find loads of visual stimuli to create the high-quality concept. This paper aims to introduce a novel AI-based method to automatically generate images as design inspiration for environment concept design. Through interviewing eight professionals, we discovered that acquiring the design stimulus with inspired “composition” in a short time is the prioritized need of designers. This paper takes spectacular ambience for example. Through testing six classic GAN model variants trained by a self-made data set, we selected qualified four models to generate black and white thumbnails as stimuli with spectacular ambience. Moreover, we conducted a qualitative study of the outputs of the four models in a manner that invite eight designers to discuss. Finally, we summarized five key factors that influence designers' satisfaction with generated visual stimuli and discuss future directions that are worth studying.
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spelling pubmed-92494552022-07-02 A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design Duan, Yingjing Zhang, Jie Comput Intell Neurosci Research Article The nature of environment concept design is a visual-based issue, where designers need to find loads of visual stimuli to create the high-quality concept. This paper aims to introduce a novel AI-based method to automatically generate images as design inspiration for environment concept design. Through interviewing eight professionals, we discovered that acquiring the design stimulus with inspired “composition” in a short time is the prioritized need of designers. This paper takes spectacular ambience for example. Through testing six classic GAN model variants trained by a self-made data set, we selected qualified four models to generate black and white thumbnails as stimuli with spectacular ambience. Moreover, we conducted a qualitative study of the outputs of the four models in a manner that invite eight designers to discuss. Finally, we summarized five key factors that influence designers' satisfaction with generated visual stimuli and discuss future directions that are worth studying. Hindawi 2022-06-24 /pmc/articles/PMC9249455/ /pubmed/35785079 http://dx.doi.org/10.1155/2022/8015492 Text en Copyright © 2022 Yingjing Duan and Jie Zhang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Duan, Yingjing
Zhang, Jie
A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design
title A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design
title_full A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design
title_fullStr A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design
title_full_unstemmed A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design
title_short A Novel AI-Based Visual Stimuli Generation Approach for Environment Concept Design
title_sort novel ai-based visual stimuli generation approach for environment concept design
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9249455/
https://www.ncbi.nlm.nih.gov/pubmed/35785079
http://dx.doi.org/10.1155/2022/8015492
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