Name
Title | ||
|---|---|---|
Semantic 3d Reconstruction With Continuous Regularization And Ray Potentials Using A Visibility Consistency Constraint |
Abstract | ||
|---|---|---|
We propose an approach for dense semantic 3D reconstruction which uses a data term that is defined as potentials over viewing rays, combined with continuous surface area penalization. Our formulation is a convex relaxation which we augment with a crucial non-convex constraint that ensures exact handling of visibility. To tackle the non-convex minimization problem, we propose a majorizeminimize type strategy which converges to a critical point. We demonstrate the benefits of using the non-convex constraint experimentally. For the geometry-only case, we set a new state of the art on two datasets of the commonly used Middlebury multi-view stereo benchmark. Moreover, our general-purpose formulation directly reconstructs thin objects, which are usually treated with specialized algorithms. A qualitative evaluation on the dense semantic 3D reconstruction task shows that we improve significantly over previous methods. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/CVPR.2016.589 | 2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) |
DocType | Volume | Issue |
Conference | abs/1604.02885 | 1 |
ISSN | Citations | PageRank |
1063-6919 | 13 | 0.57 |
References | Authors | |
33 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolay Savinov | 1 | 126 | 7.03 |
| Christian Hane | 2 | 281 | 17.03 |
| Ladický L'ubor | 3 | 1015 | 44.54 |
| Marc Pollefeys | 4 | 7671 | 475.90 |