EvIcon: Designing High-Usability Icon with Human-in-the-loop Exploration and IconCLIP

I. Chao Shen, Fu Yin Cherng*, Takeo Igarashi, Wen Chieh Lin, Bing Yu Chen

*此作品的通信作者

研究成果: Article同行評審

摘要

Interface icons are prevalent in various digital applications. Due to limited time and budgets, many designers rely on informal evaluation, which often results in poor usability icons. In this paper, we propose a unique human-in-the-loop framework that allows our target users, that is novice and professional user interface (UI) designers, to improve the usability of interface icons efficiently. We formulate several usability criteria into a perceptual usability function and enable users to iteratively revise an icon set with an interactive design tool, EvIcon. We take a large-scale pre-trained joint image-text embedding (CLIP) and fine-tune it to embed icon visuals with icon tags in the same embedding space (IconCLIP). During the revision process, our design tool provides two types of instant perceptual usability feedback. First, we provide perceptual usability feedback modelled by deep learning models trained on IconCLIP embeddings and crowdsourced perceptual ratings. Second, we use the embedding space of IconCLIP to assist users in improving icons' visual distinguishability among icons within the user-prepared icon set. To provide the perceptual prediction, we compiled IconCEPT10K, the first large-scale dataset of perceptual usability ratings over 10,000 interface icons, by conducting a crowdsourcing study. We demonstrated that our framework could benefit UI designers' interface icon revision process with a wide range of professional experience. Moreover, the interface icons designed using our framework achieved better semantic distance and familiarity, verified by an additional online user study.

原文English
文章編號e14924
期刊Computer Graphics Forum
42
發行號6
DOIs
出版狀態Published - 9月 2023

指紋

深入研究「EvIcon: Designing High-Usability Icon with Human-in-the-loop Exploration and IconCLIP」主題。共同形成了獨特的指紋。

引用此