RI: CGV: Small: Multiview Reconstruction and Calibration Using Differential Geometry of Curve Fragments and Surface Patches

RI：CGV：小：使用曲线片段和表面补丁的微分几何进行多视图重建和校准

• 批准号: 1116140
• 负责人: Benjamin Kimia
• 金额: $ 45万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1116140&HistoricalAwards=false
• 关键词: RI; CGV; Small; Multiview; Reconstruction

This project investigates the use of image curve fragments to augment the use of isolated features in multi-view calibration and reconstruction tasks. The research team develops infrastructure based on differential geometry that utilizes curves and surfaces beyond lines and planes to correlate structure in multiple images of a scene: a pair of corresponding curve fragments in two views initiates a candidate 3D curve fragment whose presence can be validated in additional views. This results in a 3D curve sketch. A significant advantage of the 3D curve sketch over an unorganized cloud of point reconstruction is that it can correlate with image curve structure in novel views without referring back to the original views. This allows both incremental reconstruction (incorporating one additional view at a time) and simultaneous reconstruction from numerous views. Calibration methods are also being explored by using curve fragments under a RANSAC regime by using differential geometry in three views or more, and differential geometry together with appearance in two views. In a similar vein the correlation of surface patches by matching observable intensity local form in images is being investigated as a method for reconstruction of local surface patches. The project provides a core technology for many applications in the computer vision field. The developed technology can be also applied to other fields such as archaeology and art.

该项目研究了如何使用图像曲线碎片来增强多视点校准和重建任务中孤立特征的使用。研究团队开发了基于微分几何的基础设施，该基础设施利用线和平面以外的曲线和曲面来关联场景的多个图像中的结构：两个视图中的一对相应的曲线片段启动了候选3D曲线片段，其存在可以在其他视图中得到验证。这将生成三维曲线草图。与无组织的点云重建相比，3D曲线草图的一个显著优势是它可以与新视图中的图像曲线结构相关联，而不需要参考原始视图。这既允许增量重建(一次合并一个额外的视图)，也允许从多个视图同时重建。在RANSAC制度下，通过在三个或更多视图中使用微分几何以及在两个视图中使用微分几何与外观一起使用曲线碎片，也在探索校准方法。在类似的脉络中，通过匹配图像中可观察到的强度局部形式来匹配表面片的相关性作为一种重建局部表面片的方法正在被研究。该项目为计算机视觉领域的许多应用提供了核心技术。开发的技术还可以应用于其他领域，如考古学和艺术。