Name
Abstract | ||
|---|---|---|
The appearance of a scene is a function of the scene contents, the lighting, and the camera pose. A set of n-pixel images of a non-degenerate scene captured from different perspectives lie on a 6D nonlinear manifold in Rn. In general, this nonlinear manifold is complicated and numerous samples are required to learn it globally. In this paper, we present a novel method and some preliminary results for incrementally tracking camera motion through sampling and linearizing the local appearance manifold. At each frame time, we use a cluster of calibrated and synchronized small baseline cameras to capture scene appearance samples at different camera poses. We compute a first-order approximation of the appearance manifold around the current camera pose. Then, as new cluster samples are captured at the next frame time, we estimate the incremental camera motion using a linear solver. By using intensity measurements and directly sampling the appearance manifold, our method avoids the commonly-used feature extraction and matching processes, and does not require 3D correspondences across frames. Thus it can be used for scenes with complicated surface materials, geometries, and view-dependent appearance properties, situations where many other camera tracking methods would fail. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/CVPR.2007.382978 | CVPR |
Keywords | Field | DocType |
image matching,nondegenerate scene,linear solver,target tracking,first-order approximation,linear programming,pixel images,motion estimation,image sampling,feature extraction,appearance manifold,matching processes,nonlinear manifold,scene appearance samples,differential camera tracking,camera motion tracking,lighting,sampling methods,parametric statistics,first order approximation,linear approximation,data mining,cluster sampling,layout | Computer vision,Pattern recognition,Computer science,Camera auto-calibration,Feature extraction,Camera resectioning,Sampling (statistics),Artificial intelligence,Linear programming,Motion estimation,Cluster sampling,Manifold | Conference |
Volume | Issue | ISSN |
2007 | 1 | 1063-6919 E-ISBN : 1-4244-1180-7 |
ISBN | Citations | PageRank |
1-4244-1180-7 | 5 | 0.71 |
References | Authors | |
15 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hua Yang | 1 | 5 | 0.71 |
| Marc Pollefeys | 2 | 7671 | 475.90 |
| Greg Welch | 3 | 1595 | 186.21 |
| Jan-Michael Frahm | 4 | 2847 | 141.20 |
| Adrian Ilie | 5 | 166 | 15.20 |