可用性
计算机科学
过程(计算)
深度学习
产品设计
人机交互
设计过程
工程设计过程
产品(数学)
人工智能
工程类
在制品
机械工程
运营管理
几何学
数学
操作系统
作者
Leijing Zhou,Xu Sun,Guannan Mu,Jiayi Wu,Jiangping Zhou,Qiuning Wu,Yaorun Zhang,Yufan Xi,Nurhan Güneş,Siyang Song
出处
期刊:IEEE Transactions on Human-Machine Systems
[Institute of Electrical and Electronics Engineers]
日期:2021-12-20
卷期号:52 (3): 445-457
被引量:3
标识
DOI:10.1109/thms.2021.3126699
摘要
Cross-cultural design requires designers to understand other foreign cultures, selecting suitable cultural elements, and finally incorporate them into product design. Traditionally, this process is time-consuming and relies to a significant extent on designers' cultural awareness and design skills. This article proposes a new tool for designers to select and integrate cultural elements in the cross-cultural design process. The proposed approach utilizes state-of-the-art deep learning techniques, which begins by automatically selecting the most suitable style image from all cultural image candidates. Then, the deep-learning-based style transfer technique is introduced to automatically produce a design image that has the same content as the uploaded design content image, and also has the cultural style of the selected style image. To the best of our knowledge, this is the first work that extends deep learning techniques to facilitate cross-cultural design. The tool received positive feedback in a usability evaluation. The empirical results show that our approach can effectively increase designers' cultural awareness in respect of four cultural element dimensions (color, material, pattern and form). It is an innovative and efficient tool to help designers with idea generation and fast prototyping, although some participants argued that the tool would only assist designers, rather than replace humans.
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