Abstract
This paper proposes a system that uses Interactive Evolutionary Computation (IEC) to recommend eyeglasses based on user aesthetic preference and suitability. The system presents the user with various eyeglasses, and the user evaluates the design based on aesthetic preference. Then, the system uses an Interactive Genetic Algorithm (IGA) to optimize the design based on the user and suitability evaluation. An experiment was conducted to determine the effectiveness of the proposed system toward optimizing eyeglass design. In the experiment, subjects were presented with two versions of the proposed system, which differed in the selection process adopted for the IGA. After system interaction, the subjects answered a questionnaire to determine any differences between the two versions. As new designs were generated, the system was could optimize the eyeglass design, to improve preference and suitability evaluations. We also found a difference in the optimization performance and user satisfaction of the two proposed methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Urai, T., Tokuamaru, M.: User Kansei clothing image retrieval system. J. Adv. Comput. Intell. Intell. Inf. 18(6), 1044–1052 (2014)
Unemi, T.: SBArt4 for an automatic evolutionary art. In: 2012 IEEE Congress on Evolutionary Computation in 2012 IEEE World Congress on Computational Intelligence (WCCI 2012), Brisbane, pp. 2014–202 (2012)
Sugahara, M., Miki, M., Hiroyasu, T.: Design of Japanese Kimono using interactive genetic algorithm. In: 2008 IEEE International Conference on Systems, Man and Cybernetics (SMC 2008), Singapore, pp. 185–190 (2008)
Sakaguchi, T., Onisawa, T.: Support system for glasses design matching user’s face. In: 27th Fuzzy System Symposium (FSS 2021), TD1-1, Fukui, pp. 597–602 (2011)
Megane no erabikata (in Japanese). https://www.jins.com/jp/guide/eyewear/select_ glasses.html. Accessed 16 Mar 2021
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Maruoka, S., Ayedoun, E., Takenouchi, H., Tokumaru, M. (2021). User Preference and Suitability-Aware Eyeglasses Recommender System. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2021 - Posters. HCII 2021. Communications in Computer and Information Science, vol 1419. Springer, Cham. https://doi.org/10.1007/978-3-030-78635-9_47
Download citation
DOI: https://doi.org/10.1007/978-3-030-78635-9_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-78634-2
Online ISBN: 978-3-030-78635-9
eBook Packages: Computer ScienceComputer Science (R0)