Browsing by Author "Igarashi, Takeo"

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    EvIcon: Designing High‐Usability Icon with Human‐in‐the‐loop Exploration and IconCLIP
    (© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Shen, I‐Chao; Cherng, Fu‐Yin; Igarashi, Takeo; Lin, Wen‐Chieh; Chen, Bing‐Yu; Hauser, Helwig and Alliez, Pierre
    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 , 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.
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    Interactive Optimization of Generative Image Modelling using Sequential Subspace Search and Content‐based Guidance
    (© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Chong, Toby; Shen, I‐Chao; Sato, Issei; Igarashi, Takeo; Benes, Bedrich and Hauser, Helwig
    Generative image modeling techniques such as GAN demonstrate highly convincing image generation result. However, user interaction is often necessary to obtain desired results. Existing attempts add interactivity but require either tailored architectures or extra data. We present a human‐in‐the‐optimization method that allows users to directly explore and search the latent vector space of generative image modelling. Our system provides multiple candidates by sampling the latent vector space, and the user selects the best blending weights within the subspace using multiple sliders. In addition, the user can express their intention through image editing tools. The system samples latent vectors based on inputs and presents new candidates to the user iteratively. An advantage of our formulation is that one can apply our method to arbitrary pre‐trained model without developing specialized architecture or data. We demonstrate our method with various generative image modelling applications, and show superior performance in a comparative user study with prior art iGAN [ZKSE16].
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    Optimizing Stepwise Animation in Dynamic Set Diagrams
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Mizuno, Kazuyo; WU, Hsiang-Yun; Takahashi, Shigeo; Igarashi, Takeo; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    A set diagram represents the membership relation among data elements. It is often visualized as secondary information on top of primary information, such as the spatial positions of elements on maps and charts. Visualizing the temporal evolution of such set diagrams as well as their primary features is quite important; however, conventional approaches have only focused on the temporal behavior of the primary features and do not provide an effective means to highlight notable transitions within the set relationships. This paper presents an approach for generating a stepwise animation between set diagrams by decomposing the entire transition into atomic changes associated with individual data elements. The key idea behind our approach is to optimize the ordering of the atomic changes such that the synthesized animation minimizes unwanted set occlusions by considering their depth ordering and reduces the gaze shift between two consecutive stepwise changes. Experimental results and a user study demonstrate that the proposed approach effectively facilitates the visual identification of the detailed transitions inherent in dynamic set diagrams.
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    Pixel Art Adaptation for Handicraft Fabrication
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Igarashi, Yuki; Igarashi, Takeo; Umetani, Nobuyuki; Wojtan, Chris; Vouga, Etienne
    Knitting and weaving patterns can be visually represented as pixel art. With hand knitting and weaving, human error (shifting, duplicating, or skipping pixels) can occur during manual fabrication. It is too costly to change already-fabricated pixels, so experts often adapt pixels that have not yet been fabricated to make the errors less visible. This paper proposes an automatic adaptation process to minimize visual artifacts. The system presents multiple adaptation possibilities to the user, who can choose the proposed adaptation or untie and re-fabricate their work. In typical handicraft fabrication, the design is complete before the start of fabrication and remains fixed during fabrication. Our system keeps updating the design during fabrication to tolerate human errors in the process. We implemented the proposed algorithm in a system that visualizes the knitting pattern, cross-stitching and bead weaving processes.