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III: Medium: Collaborative Research: Situated Visual Information Spaces

III：媒介：协作研究：情境视觉信息空间

基本信息

批准号：
2107224
负责人：
Arie Kaufman
金额：
$ 40万
依托单位：
SUNY at Stony Brook
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2107224&HistoricalAwards=false
关键词：
III Medium Collaborative Research Situated

项目摘要

The aim of this project is to enable people to effectively visualize information about the world in augmented reality. Augmented reality is potentially the next big social benefit from computer technologies, because it allows visual information to be embedded - or ‘situated’ - into the real world. This allows people using smartphones and smartglasses to see data around them in the correct real-world context. However, unlike when visualizing data on a regular computer or smartphone display, where a designer has complete control over how the application looks and feels, augmented reality visualizations are inherently overlaid on the real world. As such, visualizations must be capable of reacting to different real-world environments including dynamic scenes, and for there to be design recommendations that say how visualizations should react to different environments. This project will scientifically investigate visualization for augmented reality, study the efficacy of different approaches, create design recommendations, and then build a software system that can apply these recommendations to help design and run effective visualization applications. The proposed approach will be experimentally validated in the sports and healthcare domains.Situated visual information spaces fuse the digital information world with the physical world of objects, people, locations, and environments using augmented reality. To realize this, three scientific and design challenges will be tackled: (1) Situated visualization, interaction, and collaboration, which requires intuitive in-situ data visualizations, physical and digital interfaces for natural user interactions, and schemes for collaboration in augmented reality. Novel situated visual embedding methods will be studied for spatial and non-spatial data in dynamic environmental and situational contexts. These visualizations will automatically adapt to the physical environment, digital entities, users, and tasks while using perceptually and cognitively effective methods that do not overwhelm the user. (2) Design via constraints, where software reduces the increased complexity of creating visualizations that adapt to real-world environments. This software is aimed at visualization designers and evaluates guidelines as constraints, then balances these to provide recommendations for appropriate data and designs for the current environment. (3) Situated applications, where two wellness applications in healthcare and sports will be developed and evaluated in partnership with respective domain experts. Within them, these domains cover a spectrum of different techniques, tasks, and users. These applications will help to define an achievable research scope, drive it with motivated stakeholders, and present best-practices via use cases.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的目的是使人们能够在增强现实中有效地可视化有关世界的信息。增强现实可能是计算机技术的下一个重大社会效益，因为它允许将视觉信息嵌入或“定位”到现实世界中。这使得使用智能手机和智能眼镜的人们能够在正确的现实环境中查看周围的数据。然而，与在常规计算机或智能手机显示屏上可视化数据时不同，设计人员可以完全控制应用程序的外观和感觉，增强现实可视化本质上是覆盖在现实世界上的。因此，可视化必须能够对包括动态场景在内的不同现实世界环境做出反应，并且要有设计建议来说明可视化应如何对不同环境做出反应。该项目将科学地研究增强现实的可视化，研究不同方法的功效，创建设计建议，然后构建一个可以应用这些建议来帮助设计和运行有效的可视化应用程序的软件系统。所提出的方法将在体育和医疗保健领域进行实验验证。情境视觉信息空间使用增强现实将数字信息世界与物体、人、位置和环境的物理世界融合在一起。为了实现这一目标，需要解决三个科学和设计挑战：（1）场景可视化、交互和协作，这需要直观的现场数据可视化、自然用户交互的物理和数字界面以及增强现实中的协作方案。将研究动态环境和情境背景下的空间和非空间数据的新颖的情境视觉嵌入方法。这些可视化将自动适应物理环境、数字实体、用户和任务，同时使用不会让用户不知所措的感知和认知有效方法。 (2) 通过约束进行设计，软件降低了创建适应现实环境的可视化的复杂性。该软件面向可视化设计人员，评估指导方针作为约束，然后平衡这些指导方针，为当前环境的适当数据和设计提供建议。 (3) 定位应用程序，其中医疗保健和体育领域的两个健康应用程序将与各自领域的专家合作开发和评估。其中，这些领域涵盖了一系列不同的技术、任务和用户。这些应用程序将有助于定义可实现的研究范围，与积极的利益相关者一起推动研究范围，并通过用例展示最佳实践。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（13）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

NeuRegenerate: A Framework for Visualizing Neurodegeneration

DOI：
10.1109/tvcg.2021.3127132
发表时间：
2021-11
期刊：
IEEE Transactions on Visualization and Computer Graphics
影响因子：
5.2
作者：
S. Boorboor;Shawn Mathew;M. Ananth;D. Talmage;L. Role;A. Kaufman
通讯作者：
S. Boorboor;Shawn Mathew;M. Ananth;D. Talmage;L. Role;A. Kaufman

Risk Perception and Preparation for Storm Surge Flooding: A Virtual Workshop with Visualization and Stakeholder Interaction

风暴潮洪水的风险感知和准备：具有可视化和利益相关者互动的虚拟研讨会

DOI：
10.1175/bams-d-22-0145.1
发表时间：
2023
期刊：
Bulletin of the American Meteorological Society
影响因子：
8
作者：
Colle, Brian A.;Hathaway, Julia R.;Bojsza, Elizabeth J.;Moses, Josef M.;Sanders, Shadya J.;Rowan, Katherine E.;Hils, Abigail L.;Duesterhoeft, Elizabeth C.;Boorboor, Saeed;Kaufman, Arie E.
通讯作者：
Kaufman, Arie E.

Autonomous Aesthetic Views Finding in Indoor Scenes with Deep Reinforcement Learning

通过深度强化学习在室内场景中寻找自主审美观