Collaborative Research: CCRI: Planning: InfraStructure for Photorealistic Image and Environment Synthesis (I-SPIES)

合作研究：CCRI：规划：真实感图像和环境合成的基础设施 (I-SPIES)

• 批准号: 2120235
• 负责人: Nicholas Gans
• 金额: $ 1.29万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120235&HistoricalAwards=false
• 关键词: Collaborative; Research; CCRI; Planning; InfraStructure

Numerous Computer and Information Science and Engineering (CISE) research communities leverage datasets comprised of visual images or 3D virtual environments to conduct research in computer vision, robotics, multimedia systems, virtual reality, and mixed reality. Many of these datasets consist of either images previously captured with cameras and other optical sensors, or synthetic images previously rendered from 3D virtual environments. The static nature of these datasets limits their usefulness and potential applications. Recently, some researchers have provided datasets and tools for synthesizing new images from 3D virtual environments using customizable virtual camera positions, which broadens their research applications. However, many of these datasets consist of lower-fidelity indoor virtual environments that yield non-photorealistic images. Furthermore, such datasets are missing outdoor virtual environments, and tools for sharing custom camera positions within the research community are not currently available.This planning project prepares to address the limitations of prior datasets by investigating the feasibility of using high-quality terrestrial laser scanners to capture and create high-fidelity, photorealistic virtual environments of real-world locations, both indoor and outdoor. This will be coupled with surveys of the relevant CISE research communities through workshops held at top academic conferences. This project will result in the development of two preliminary datasets, one indoor and one outdoor, using the proposed laser-scanner methodology, and the identification of community needs, priorities, and support for the proposed InfraStructure for Photorealistic Images and Environment Synthesis (I-SPIES). Undergraduate students will be engaged in the development of the preliminary datasets through the University of Central Florida’s EXCEL STEM program, a former NSF STEP programThis 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.

许多计算机，信息和工程（CISE）级别数据集由视觉图像或3D虚拟熨斗，用于计算机视觉，机器人技术，多媒体系统，虚拟现实和混合现实。从3D虚拟环境中启用了其有用性和潜在的应用程序。影像图像，此类数据集缺少户外虚拟环境，并且在研究社区中共享自定义AMERA的工具不是当前使用优先级的局限性的局限性通过在顶级学术会议上对室内和室外的富豪地点。对光图像图像的需求，优先级和支持（合成I-Spies）将是英语数据集中的中心depsets of Centralida of Centralida的L STEM计划，这是前NSF Step Programs，这是NSF Thalugh使用Toundatuntelectu al功绩和更广泛的影响审查标准进行评估。