Name
Abstract | ||
|---|---|---|
We introduce the distributed camera model, a novel model for Structure-from-Motion (SfM). This model describes image observations in terms of light rays with ray origins and directions rather than pixels. As such, the proposed model is capable of describing a single camera or multiple cameras simultaneously as the collection of all light rays observed. We show how the distributed camera model is a generalization of the standard camera model and we describe a general formulation and solution to the absolute camera pose problem that works for standard or distributed cameras. The proposed method computes a solution that is up to 8 times more efficient and robust to rotation singularities in comparison with gDLS[21]. Finally, this method is used in an novel large-scale incremental SfM pipeline where distributed cameras are accurately and robustly merged together. This pipeline is a direct generalization of traditional incremental SfM, however, instead of incrementally adding one camera at a time to grow the reconstruction the reconstruction is grown by adding a distributed camera. Our pipeline produces highly accurate reconstructions efficiently by avoiding the need for many bundle adjustment iterations and is capable of computing a 3D model of Rome from over 15,000 images in just 22 minutes. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/3DV.2016.31 | 2016 Fourth International Conference on 3D Vision (3DV) |
Keywords | DocType | Volume |
3d reconstruction,structure from motion,camera calibration | Conference | abs/1607.03949 |
ISSN | ISBN | Citations |
2378-3826 | 978-1-5090-5408-4 | 4 |
PageRank | References | Authors |
0.38 | 23 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chris Sweeney | 1 | 101 | 7.42 |
| Victor Fragoso | 2 | 74 | 5.51 |
| Tobias Höllerer | 3 | 2666 | 244.50 |
| Matthew Turk | 4 | 3724 | 499.42 |