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

Brown University, Providence RI

Investigators

Abstract

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.