Name
Abstract | ||
|---|---|---|
A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate. |
Year | Venue | Keywords |
|---|---|---|
2011 | ISVC (1) | image domain,high-quality terrain reconstruction,orthographic stereo correlator,ames stereo pipeline,consecutive amc image pair,image pair,local terrain,back-projected image,terrain model,apollo metric image,elevation estimate,correlation window,nasa ames intelligent robotics,3d reconstruction,moon,image processing,digital elevation models,orthography,stereoscopic vision,selenography |
Field | DocType | Citations |
Computer vision,Stereo camera,Computer graphics (images),Bundle adjustment,Computer science,Stereopsis,Terrain,Image processing,Digital elevation model,Artificial intelligence,Raised-relief map,3D reconstruction | Conference | 0 |
PageRank | References | Authors |
0.34 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taemn Kim | 1 | 382 | 28.18 |
| Kyle Husmann | 2 | 0 | 0.34 |
| Zachary Moratto | 3 | 7 | 1.94 |
| Ara V. Nefian | 4 | 751 | 56.08 |