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: 0964027
• 负责人: Noah Snavely
• 金额: $ 24万
• 依托单位: Cornell University
• 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 2014-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0964027&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生产非常详细和准确的三维几何和外观（BRDF）模型在城市规模从互联网上收集的照片从各种来源包含数百万张照片的巨大多样性，如观看范围和条件，一天中的时间和天气条件，仅举几例。 城市场景的属性可能包括低纹理表面，反射和透明材料，以及挑战现有重建算法的重复结构。调查人员将应对这些挑战，目的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能被合并。 有一些研究课题与该项目有关。为了在城市规模上注册照片并恢复稀疏几何形状，将设计一种新的统一的运动恢复结构（SfM）算法，以利用大型并行计算平台。 多视点立体（MVS）算法利用配准的照片和SfM恢复的稀疏三维场景点，可以重建出详细的几何模型。 新的MVS算法将利用建筑场景的结构和体积重建方法将被用来产生特殊的精度和可用性的注释模型。数字模型在社会、文化和经济奋进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。 所有模型和数据集将免费提供给研究人员和公众。