RI: Medium: Collaborative Research: Reconstructing Cities from Photographs

RI：媒介：合作研究：从照片重建城市

• 批准号: 0963743
• 负责人: Bernard Frischer
• 金额: $ 24万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-15 至 2013-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0963743&HistoricalAwards=false
• 关键词: RI; Medium; Collaborative; Research; Reconstructing

This project is focused on research issues associated with producing extremely detailed and accurate 3D geometry and appearance (BRDF) models at city scale from internet collections of photos from various sources containing millions of photos of enormous diversity such as viewing range and conditions, time of day and weather conditions, to name a few. The properties of urban scenes may include low-texture surfaces, reflective and transparent materials, and repeated structures that challenge existing reconstruction algorithms. The investigators will address these challenges with the aim of reconstructing several large US and foreign cities. Historical photos and virtual models may also be incorporated. There are a number of research topics associated with the project. To register photographs and recover sparse geometry at city-scale, a new, unified, structure-from-motion (SfM) algorithm will be designed to take advantage of large, parallel computing platforms. With registered photographs and sparse 3D scene points recovered by SfM, multi-view stereo (MVS) algorithms can reconstruct detailed geometric models. Novel MVS algorithms will then exploit the structure of architectural scenes and volumetric reconstruction methods will be employed to produce annotated models of exceptional accuracy and usability. Digital models are playing an increasingly important role in social, cultural and economic endeavor and are central to next-generation mapping and visualization applications. All models and datasets will be made freely available to researchers and the general public.

该项目的重点是研究与从各种来源的互联网照片集中生成城市规模的极其详细和准确的 3D 几何和外观 (BRDF) 模型相关的问题，这些照片包含数百万张具有巨大多样性的照片，例如观看范围和条件、一天中的时间以及天气状况等等。 城市场景的属性可能包括低纹理表面、反光和透明材料以及挑战现有重建算法的重复结构。调查人员将解决这些挑战，目标是重建美国和外国的几个大城市。 历史照片和虚拟模型也可以被合并。 有许多与该项目相关的研究主题。为了在城市尺度上配准照片并恢复稀疏几何形状，将设计一种新的、统一的运动结构 (SfM) 算法，以利用大型并行计算平台。 通过配准照片和 SfM 恢复的稀疏 3D 场景点，多视图立体 (MVS) 算法可以重建详细的几何模型。 然后，新颖的 MVS 算法将利用建筑场景的结构，并采用体积重建方法来生成具有卓越准确性和可用性的带注释模型。数字模型在社会、文化和经济活动中发挥着越来越重要的作用，是下一代地图和可视化应用的核心。 所有模型和数据集都将免费提供给研究人员和公众。