IEEE Computer Graphics and Applications最新文献

Design Exploration of AI-Assisted Personal Affective Physicalization. 人工智能辅助个人情感物质化的设计探索。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-26 DOI: 10.1109/MCG.2025.3614686

Ruishan Wu, Zhuoyang Li, Charles Perin, Sheelagh Carpendale, Can Liu

引用次数: 0

Towards softerware: Enabling personalization of interactive data representations for users with disabilities. 走向软件：为残疾用户实现交互式数据表示的个性化。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-12 DOI: 10.1109/MCG.2025.3609294

Frank Elavsky, Marita Vindedal, Ted Gies, Patrick Carrington, Dominik Moritz, Oystein Moseng

{"title":"Towards softerware: Enabling personalization of interactive data representations for users with disabilities.","authors":"Frank Elavsky, Marita Vindedal, Ted Gies, Patrick Carrington, Dominik Moritz, Oystein Moseng","doi":"10.1109/MCG.2025.3609294","DOIUrl":"https://doi.org/10.1109/MCG.2025.3609294","url":null,"abstract":"Accessible design for some may still produce barriers for others. This tension, called access friction, creates challenges for both designers and end-users with disabilities. To address this, we present the concept of softerware, a system design approach that provides end users with agency to meaningfully customize and adapt interfaces to their needs. To apply softerware to visualization, we assembled 195 data visualization customization options centered on the barriers we expect users with disabilities will experience. We built a prototype that applies a subset of these options and interviewed practitioners for feedback. Lastly, we conducted a design probe study with blind and low vision accessibility professionals to learn more about their challenges and visions for softerware. We observed access frictions between our participant's designs and they expressed that for softerware's success, current and future systems must be designed with accessible defaults, interoperability, persistence, and respect for a user's perceived effort-to-outcome ratio.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"PP ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145056047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Agentic Visualization: Extracting Agent-based Design Patterns from Visualization Systems. 代理可视化：从可视化系统中提取基于代理的设计模式。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-09 DOI: 10.1109/MCG.2025.3607741

Vaishali Dhanoa, Anton Wolter, Gabriela Molina Leon, Hans-Jorg Schulz, Niklas Elmqvist

引用次数: 0

Virtual Staging of Indoor Panoramic Images via Multi-task Learning and Inverse Rendering. 基于多任务学习和反向渲染的室内全景图像虚拟舞台。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-03 DOI: 10.1109/MCG.2025.3605806

Uzair Shah, Sara Jashari, Muhammad Tukur, Mowafa Househ, Jens Schneider, Giovanni Pintore, Enrico Gobbetti, Marco Agus

{"title":"Virtual Staging of Indoor Panoramic Images via Multi-task Learning and Inverse Rendering.","authors":"Uzair Shah, Sara Jashari, Muhammad Tukur, Mowafa Househ, Jens Schneider, Giovanni Pintore, Enrico Gobbetti, Marco Agus","doi":"10.1109/MCG.2025.3605806","DOIUrl":"https://doi.org/10.1109/MCG.2025.3605806","url":null,"abstract":"Capturing indoor environments with 360° images provides a cost-effective method for creating immersive content. However, virtual staging - removing existing furniture and inserting new objects with realistic lighting - remains challenging. We present VISPI (Virtual Staging Pipeline for Single Indoor Panoramic Images), a framework that enables interactive restaging of indoor scenes from a single panoramic image. Our approach combines multi-task deep learning with real-time rendering to extract geometric, semantic, and material information from cluttered scenes. The system includes: i) a vision transformer that simultaneously predicts depth, normals, semantics, albedo, and material properties; ii) spherical Gaussian lighting estimation; iii) real-time editing for interactive object placement; iv) stereoscopic Multi-Center-Of-Projection generation for Head Mounted Display exploration. The framework processes input through two pathways: extracting clutter-free representations for virtual staging and estimating material properties including metallic and roughness signals. We evaluate VISPI on Structured3D and FutureHouse datasets, demonstrating applications in real estate visualization, interior design, and virtual environment creation.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"PP ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144994462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tooth Completion and Reconstruction in Digital Orthodontics. 数字正畸的牙齿补全与重建。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-02 DOI: 10.1109/MCG.2025.3605266

Hao Yu, Longdu Liu, Shuangmin Chen, Shiqing Xin, Changhe Tu

引用次数: 0

A Cosmic View of Life on Earth: Hierarchical Visualization of Biological Data Using Astronomical Software. 地球生命的宇宙观：使用天文软件的生物数据分层可视化。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-01 DOI: 10.1109/MCG.2025.3591713

Wandrille Duchemin, Takanori Fujiwara, Hollister W Herhold, Elias Elmquist, David S Thaler, William Harcourt-Smith, Emma Broman, Alexander Bock, Brian P Abbott, Jacqueline K Faherty

{"title":"A Cosmic View of Life on Earth: Hierarchical Visualization of Biological Data Using Astronomical Software.","authors":"Wandrille Duchemin, Takanori Fujiwara, Hollister W Herhold, Elias Elmquist, David S Thaler, William Harcourt-Smith, Emma Broman, Alexander Bock, Brian P Abbott, Jacqueline K Faherty","doi":"10.1109/MCG.2025.3591713","DOIUrl":"10.1109/MCG.2025.3591713","url":null,"abstract":"A goal of data visualization is to advance the understanding of multiparameter, large-scale datasets. In astrophysics, scientists map celestial objects to understand the hierarchical structure of the universe. In biology, genetic sequences and biological characteristics uncover evolutionary relationships and patterns (e.g., variation within species and ecological associations). Our highly interdisciplinary project entitled \"A Cosmic View of Life on Earth\" adapts an immersive astrophysics visualization platform called OpenSpace to contextualize diverse biological data. Dimensionality reduction techniques harmonize biological information to create spatial representations in which data are interactively explored on flat screens and planetarium domes. Visualizations are enriched with geographic metadata, 3-D scans of specimens, and species-specific sonifications (e.g., bird songs). The \"Cosmic View\" project eases the dissemination of stories related to biological domains (e.g., insects, birds, mammals, and human migrations) and facilitates scientific discovery.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"PP ","pages":"93-106"},"PeriodicalIF":1.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ProHap Explorer: Visualizing Haplotypes in Proteogenomic Datasets. ProHap Explorer：可视化蛋白质基因组数据集中的单倍型。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-01 DOI: 10.1109/MCG.2025.3581736

Jakub Vasicek, Dafni Skiadopoulou, Ksenia G Kuznetsova, Lukas Kall, Marc Vaudel, Stefan Bruckner

{"title":"ProHap Explorer: Visualizing Haplotypes in Proteogenomic Datasets.","authors":"Jakub Vasicek, Dafni Skiadopoulou, Ksenia G Kuznetsova, Lukas Kall, Marc Vaudel, Stefan Bruckner","doi":"10.1109/MCG.2025.3581736","DOIUrl":"10.1109/MCG.2025.3581736","url":null,"abstract":"In mass spectrometry-based proteomics, experts usually project data onto a single set of reference sequences, overlooking the influence of common haplotypes (combinations of genetic variants inherited together from a parent). We recently introduced ProHap, a tool for generating customized protein haplotype databases. Here, we present ProHap Explorer, a visualization interface designed to investigate the influence of common haplotypes on the human proteome. It enables users to explore haplotypes, their effects on protein sequences, and the identification of noncanonical peptides in public mass spectrometry datasets. The design builds on well-established representations in biological sequence analysis, ensuring familiarity for domain experts while integrating novel interactive elements tailored to proteogenomic data exploration. User interviews with proteomics experts confirmed the tool's utility, highlighting its ability to reveal whether haplotypes affect proteins of interest. By facilitating the intuitive exploration of proteogenomic variation, ProHap Explorer supports research in personalized medicine and the development of targeted therapies.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"PP ","pages":"64-77"},"PeriodicalIF":1.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Designing for Collaboration: Visualization to Enable Human-LLM Analytical Partnership. 协作设计：可视化实现人-法学硕士分析伙伴关系。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-01 DOI: 10.1109/MCG.2025.3583451

Mai Elshehaly, Radu Jianu, Aidan Slingsby, Gennady Andrienko, Natalia Andrienko, Theresa-Marie Rhyne

{"title":"Designing for Collaboration: Visualization to Enable Human-LLM Analytical Partnership.","authors":"Mai Elshehaly, Radu Jianu, Aidan Slingsby, Gennady Andrienko, Natalia Andrienko, Theresa-Marie Rhyne","doi":"10.1109/MCG.2025.3583451","DOIUrl":"https://doi.org/10.1109/MCG.2025.3583451","url":null,"abstract":"Visualization artifacts have long served as anchors for collaboration and knowledge transfer in data analysis. While effective for human-human collaboration, little is known about their role in capturing and externalizing knowledge when working with large language models (LLMs). Despite the growing role of LLMs in analytics, their linear text-based workflows limit the ability to structure artifacts into useful and traceable representations of the analytical process. We argue that dynamic visual representations of evolving analysis-organizing artifacts and provenance into semantic structures, such as idea development and shifts in inquiry-are critical for effective human-LLM workflows. We demonstrate the current opportunities and limitations of using LLMs to track, structure, and visualize analytic processes, and propose a research agenda to leverage rapid advances in LLM capabilities. Our goal is to present a compelling argument for maximizing the role of visualization as a catalyst for more structured, transparent, and insightful human-LLM analytical interactions.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"45 5","pages":"107-116"},"PeriodicalIF":1.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145193786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AuraGenome: An LLM-Powered Framework for On-the-Fly Reusable and Scalable Circular Genome Visualizations. AuraGenome：一个llm驱动的框架，用于动态可重用和可扩展的圆形基因组可视化。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-01 DOI: 10.1109/MCG.2025.3581560

Chi Zhang, Yu Dong, Yang Wang, Yuetong Han, Guihua Shan, Bixia Tang

{"title":"AuraGenome: An LLM-Powered Framework for On-the-Fly Reusable and Scalable Circular Genome Visualizations.","authors":"Chi Zhang, Yu Dong, Yang Wang, Yuetong Han, Guihua Shan, Bixia Tang","doi":"10.1109/MCG.2025.3581560","DOIUrl":"10.1109/MCG.2025.3581560","url":null,"abstract":"Circular genome visualizations are essential for exploring structural variants and gene regulation. However, existing tools often require complex scripting and manual configuration, making the process time-consuming, error-prone, and difficult to learn. To address these challenges, we introduce AuraGenome, a large language model (LLM)-powered framework for rapid, reusable, and scalable generation of multilayered circular genome visualizations. AuraGenome combines a semantic-driven multiagent workflow with an interactive visual analytics system. The workflow employs seven specialized LLM-driven agents, each assigned distinct roles, such as intent recognition, layout planning, and code generation, to transform raw genomic data into tailored visualizations. The system supports multiple coordinated views tailored for genomic data, offering ring, radial, and chord-based layouts to represent multilayered circular genome visualizations. In addition to enabling interactions and configuration reuse, the system supports real-time refinement and high-quality report export. We validate its effectiveness through two case studies and a comprehensive user study. AuraGenome is available at https://github.com/Darius18/AuraGenome.","PeriodicalId":55026,"journal":{"name":"IEEE Computer Graphics and Applications","volume":"PP ","pages":"78-92"},"PeriodicalIF":1.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Circuit Mining in Transcriptomics Data. 转录组学数据中的电路挖掘。

IF 1.4 4区计算机科学

IEEE Computer Graphics and Applications Pub Date : 2025-09-01 DOI: 10.1109/MCG.2025.3594562

Tobias Peherstorfer, Sophia Ulonska, Bianca Burger, Simone Lucato, Bader Al-Hamdan, Marvin Kleinlehner, Till F M Andlauer, Katja Buhler

引用次数: 0