Proceedings of the 2nd International Conference on Intelligent Design and Innovative Technology (ICIDIT 2023)

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A Study on the Correlation Analysis between Product Cognitive Features and Visual Features

Authors
Zhuen Guo1, Li Lin1, *
1School of Mechanical Engineering, Guizhou University, Guiyang, Guizhou, 550025, China
*Corresponding author. Email: 715842042@qq.com
Corresponding Author
Li Lin
Available Online 10 October 2023.
DOI
10.2991/978-94-6463-266-8_26How to use a DOI?
Keywords
Design Features; Eye-Tracking Tests; Grad-CAM
Abstract

Obtaining key feature elements based on design requirements is a fundamental task in the product design process. To explore the role of feature recognition in product design in algorithmic classification. This study explores the feasibility of using algorithmically derived product visual features to replace traditional methods for acquiring key product features by analyzing the correlation between user cognitive data obtained from eye tracking tests and visual data derived from category mapping activations based on algorithms. To begin, eye tracking tests are conducted to understand users' cognitive processes when viewing product images under different emotional objectives, and the findings are visualized through heatmaps. Subsequently, the ResNet34 classification algorithm is applied for image classification training, incorporating the Grad CAM visualization layer to obtain the visual feature data of product images. An association analysis is performed on the significant features obtained through both approaches. Finally, a conclusion is drawn regarding the feasibility of obtaining key product feature data based on the algorithmic model.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Conference on Intelligent Design and Innovative Technology (ICIDIT 2023)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
10 October 2023
ISBN
10.2991/978-94-6463-266-8_26
ISSN
2589-4919
DOI
10.2991/978-94-6463-266-8_26How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zhuen Guo
AU  - Li Lin
PY  - 2023
DA  - 2023/10/10
TI  - A Study on the Correlation Analysis between Product Cognitive Features and Visual Features
BT  - Proceedings of the 2nd International Conference on Intelligent Design and Innovative Technology (ICIDIT 2023)
PB  - Atlantis Press
SP  - 234
EP  - 240
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-266-8_26
DO  - 10.2991/978-94-6463-266-8_26
ID  - Guo2023
ER  -