Shape Generation System for Optimizing Aesthetic Interest associated with Novelty and Complexity

DS 122: Proceedings of the Design Society: 24th International Conference on Engineering Design (ICED23)

Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author: Honda, Shimon; Yanagisawa, Hideyoshi
Series: ICED
Institution: The University of Tokyo
Section: Design Methods
Page(s): 3155-3164
DOI number: https://doi.org/10.1017/pds.2023.316
ISBN: -
ISSN: -

Abstract

Design aesthetics are one of the most important factors affecting the attractiveness of industrial products. Psychological theory suggests that a moderate level of novelty and complexity yields pleasant feelings in users. A design that is initially surprising to consumers and acceptable over time requires aesthetic interest associated with its novelty and complexity. In this study, we formulated the perceived novelty and complexity of a closed contour shape. Based on this formulation, we developed "Hybrid-GAN," which is a shape-generation system capable of generating a variety of shapes of arbitrary novelty and complexity. In a series of experiment, we obtained subjective evaluations of novelty and complexity, as well as beauty and interest, for the generated shape samples. The results indicated that our novelty and complexity formulations had significant positive correlations with subjective evaluations. The sum of the formulated novelty and complexity also had a significant positive correlation with interest. The results of this study are expected to be used to support the design of attractive shapes by providing feedback to designers regarding the degrees of novelty and complexity that users find most pleasant.

Keywords: Design for X (DfX), Design engineering, Complexity, Computational design methods

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