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

该项目研究了图像曲线碎片的使用，以增强多视图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：两个视图中的一对对应曲线片段启动候选3D曲线片段，其存在可以在其他视图中进行验证。这将产生一个3D曲线草图。与无组织的点云重建相比，三维曲线草图的一个显著优势是，它可以在不参考原始视图的情况下与新视图中的图像曲线结构相关联。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。校准方法也在探索中，通过在三个视图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和外观，在RANSAC制度下使用曲线片段。同样，通过匹配图像中的可观察强度局部形式来研究表面斑块的相关性，作为局部表面斑块重建的一种方法。该项目为计算机视觉领域的许多应用提供了核心技术。发达的技术也可以应用于其他领域，如考古和艺术。

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.