Name
Abstract | ||
|---|---|---|
This paper deals with surface normal estimation from calibrated stereo images. We show here how the affine transformation between two projections defines the surface normal of a 3D planar patch. We give a formula that describes the relationship of surface normals, camera projections, and affine transformations. This formula is general since it works for every kind of cameras. We propose novel methods for estimating the normal of a surface patch if the affine transformation is known between two perspective images. We show here that the normal vector can be optimally estimated if the projective depth of the patch is known. Other non-optimal methods are also introduced for the problem. The proposed methods are tested both on synthesized data and images of real-world 3D objects. |
Year | Venue | Field |
|---|---|---|
2015 | VISAPP | Affine transformation,Computer vision,Affine geometry,Affine shape adaptation,Harris affine region detector,Affine combination,Affine coordinate system,Artificial intelligence,Affine plane,Affine hull,Mathematics |
DocType | Citations | PageRank |
Conference | 1 | 0.35 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Barath | 1 | 3 | 1.04 |
| József Molnár | 2 | 31 | 3.95 |
| Levente Hajder | 3 | 43 | 12.55 |