IEEE transactions on visualization and computer graphics最新文献_第2页

2024 VGTC Visualization Technical Achievement Award 2024 年 VGTC 可视化技术成就奖

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-25 DOI: 10.1109/TVCG.2024.3473368

Han-Wei Shen;Bongshin Lee

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VIS 2024 Program Committee VIS 2024 计划委员会

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-25 DOI: 10.1109/TVCG.2024.3473331

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2024 VGTC Visualization Service Award 2024 年 VGTC 可视化服务奖

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-25 DOI: 10.1109/TVCG.2024.3473208

Maria Vélez

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2024 VGTC Visualization Dissertation Award 2024 VGTC 可视化论文奖

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-25 DOI: 10.1109/TVCG.2024.3473168

Lin Yan

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2024 VGTC Visualization Lifetime Achievement Award 2024 VGTC 可视化终身成就奖

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-22 DOI: 10.1109/TVCG.2024.3473189

Hans-Christian Hege;Min Chen

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Visualization-Driven Illumination for Density Plots. 可视化驱动的密度图照明。

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-11 DOI: 10.1109/TVCG.2024.3495695

Xin Chen, Yunhai Wang, Huaiwei Bao, Kecheng Lu, Jaemin Jo, Chi-Wing Fu, Jean-Daniel Fekete

{"title":"Visualization-Driven Illumination for Density Plots.","authors":"Xin Chen, Yunhai Wang, Huaiwei Bao, Kecheng Lu, Jaemin Jo, Chi-Wing Fu, Jean-Daniel Fekete","doi":"10.1109/TVCG.2024.3495695","DOIUrl":"https://doi.org/10.1109/TVCG.2024.3495695","url":null,"abstract":"We present a novel visualization-driven illumination model for density plots, a new technique to enhance density plots by effectively revealing the detailed structures in high- and medium-density regions and outliers in low-density regions, while avoiding artifacts in the density field's colors. When visualizing large and dense discrete point samples, scatterplots and dot density maps often suffer from overplotting, and density plots are commonly employed to provide aggregated views while revealing underlying structures. Yet, in such density plots, existing illumination models may produce color distortion and hide details in low-density regions, making it challenging to look up density values, compare them, and find outliers. The key novelty in this work includes (i) a visualization-driven illumination model that inherently supports density-plot-specific analysis tasks and (ii) a new image composition technique to reduce the interference between the image shading and the color-encoded density values. To demonstrate the effectiveness of our technique, we conducted a quantitative study, an empirical evaluation of our technique in a controlled study, and two case studies, exploring twelve datasets with up to two million data point samples.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Investigating the Potential of Haptic Props for 3D Object Manipulation in Handheld AR. 探究手持式 AR 中触觉道具对 3D 物体操作的潜力

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-11 DOI: 10.1109/TVCG.2024.3495021

Jonathan Wieland, Maximilian Durr, Rebecca Frisch, Melissa Michalke, Dominik Morgenstern, Harald Reiterer, Tiare Feuchtner

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"where Did My Apps Go?" Supporting Scalable and Transition-Aware Access to Everyday Applications in Head-Worn Augmented Reality. "我的应用程序去哪儿了？在头戴式增强现实中支持可扩展和过渡感知的日常应用访问。

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-08 DOI: 10.1109/TVCG.2024.3493115

Feiyu Lu, Leonardo Pavanatto, Shakiba Davari, Lei Zhang, Lee Lisle, Doug A Bowman

{"title":"\"where Did My Apps Go?\" Supporting Scalable and Transition-Aware Access to Everyday Applications in Head-Worn Augmented Reality.","authors":"Feiyu Lu, Leonardo Pavanatto, Shakiba Davari, Lei Zhang, Lee Lisle, Doug A Bowman","doi":"10.1109/TVCG.2024.3493115","DOIUrl":"https://doi.org/10.1109/TVCG.2024.3493115","url":null,"abstract":"Future augmented reality (AR) glasses empower users to view personal applications and services anytime and anywhere without being restricted by physical locations and the availability of physical screens. In typical everyday activities, people move around to carry out different tasks and need a variety of information on the go. Existing interfaces in AR do not support these use cases well, especially when the number of applications increases. We explore the usability of three world-referenced approaches that move AR applications with users as they transition among different locations, featuring different levels of AR app availability: (1) always using a menu to manually open an app when needed; (2) automatically suggesting a relevant subset of all apps; and (3) carrying all apps with the users to the new location. Through a controlled study and a relatively more ecologically-valid study in AR, we reached better understandings on the performance trade-offs and observed the impact of various everyday contextual factors on these interfaces in more realistic AR settings. Our results shed light on how to better support the mobile information needs of users in everyday life in future AR interfaces.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PGSR: Planar-based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstruction. PGSR：基于平面高斯拼接技术的高效高保真曲面重构。

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-07 DOI: 10.1109/TVCG.2024.3494046

Danpeng Chen, Hai Li, Weicai Ye, Yifan Wang, Weijian Xie, Shangjin Zhai, Nan Wang, Haomin Liu, Hujun Bao, Guofeng Zhang

{"title":"PGSR: Planar-based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstruction.","authors":"Danpeng Chen, Hai Li, Weicai Ye, Yifan Wang, Weijian Xie, Shangjin Zhai, Nan Wang, Haomin Liu, Hujun Bao, Guofeng Zhang","doi":"10.1109/TVCG.2024.3494046","DOIUrl":"https://doi.org/10.1109/TVCG.2024.3494046","url":null,"abstract":"Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is difficult to guarantee geometric reconstruction accuracy and multi-view consistency simply by relying on image reconstruction loss. Although many studies on surface reconstruction based on 3DGS have emerged recently, the quality of their meshes is generally unsatisfactory. To address this problem, we propose a fast planar-based Gaussian splatting reconstruction representation (PGSR) to achieve high-fidelity surface reconstruction while ensuring high-quality rendering. Specifically, we first introduce an unbiased depth rendering method, which directly renders the distance from the camera origin to the Gaussian plane and the corresponding normal map based on the Gaussian distribution of the point cloud, and divides the two to obtain the unbiased depth. We then introduce single-view geometric, multi-view photometric, and geometric regularization to preserve global geometric accuracy. We also propose a camera exposure compensation model to cope with scenes with large illumination variations. Experiments on indoor and outdoor scenes show that the proposed method achieves fast training and rendering while maintaining high-fidelity rendering and geometric reconstruction, outperforming 3DGS-based and NeRF-based methods. Our code will be made publicly available, and more information can be found on our project page (https://zju3dv.github.io/pgsr/).","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

From Dashboard Zoo to Census: A Case Study With Tableau Public. 从仪表盘动物园到人口普查：使用 Tableau Public 的案例研究。

IEEE transactions on visualization and computer graphics Pub Date : 2024-11-06 DOI: 10.1109/TVCG.2024.3490259

Arjun Srinivasan, Joanna Purich, Michael Correll, Leilani Battle, Vidya Setlur, Anamaria Crisan

{"title":"From Dashboard Zoo to Census: A Case Study With Tableau Public.","authors":"Arjun Srinivasan, Joanna Purich, Michael Correll, Leilani Battle, Vidya Setlur, Anamaria Crisan","doi":"10.1109/TVCG.2024.3490259","DOIUrl":"https://doi.org/10.1109/TVCG.2024.3490259","url":null,"abstract":"Dashboards remain ubiquitous tools for analyzing data and disseminating the findings. Understanding the range of dashboard designs, from simple to complex, can support development of authoring tools that enable end-users to meet their analysis and communication goals. Yet, there has been little work that provides a quantifiable, systematic, and descriptive overview of dashboard design patterns. Instead, existing approaches only consider a handful of designs, which limits the breadth of patterns that can be surfaced. More quantifiable approaches, inspired by machine learning (ML), are presently limited to single visualizations or capture narrow features of dashboard designs. To address this gap, we present an approach for modeling the content and composition of dashboards using a graph representation. The graph decomposes dashboard designs into nodes featuring content \"blocks'; and uses edges to model \"relationships\", such as layout proximity and interaction, between nodes. To demonstrate the utility of this approach, and its extension over prior work, we apply this representation to derive a census of 25,620 dashboards from Tableau Public, providing a descriptive overview of the core building blocks of dashboards in the wild and summarizing prevalent dashboard design patterns. We discuss concrete applications of both a graph representation for dashboard designs and the resulting census to guide the development of dashboard authoring tools, making dashboards accessible, and for leveraging AI/ML techniques. Our findings underscore the importance of meeting users where they are by broadly cataloging dashboard designs, both common and exotic.","PeriodicalId":94035,"journal":{"name":"IEEE transactions on visualization and computer graphics","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142591899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0