Name
Title | ||
|---|---|---|
A Fast And Robust Solution To The Five-Point Relative Pose Problem Using Gauss-Newton Optimization On A Manifold |
Abstract | ||
|---|---|---|
Extracting the motion parameters of a moving camera is an important issue in computer vision. This is due to the need of numerous emerging applications like telepresence and robot navigation. The key issue is to determine a robust estimate of the (30) essential matrix with its five degrees of freedom. In this work, a robust technique to compute the essential matrix is suggested under the assumption that the images are calibrated. The algorithm is a combination of the five-point relative pose problem using an optimization technique on a manifold, with the random sample consensus. The results show that the proposed method delivers faster and more accurate results than the standard techniques. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICASSP.2007.365999 | 2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PTS 1-3, PROCEEDINGS |
Keywords | Field | DocType |
differential geometry, iterative methods, machine vision | Computer vision,Mathematical optimization,Essential matrix,Machine vision,Iterative method,Computer science,Artificial intelligence,Motion estimation,Estimation theory,Robot,Manifold,Newton's method | Conference |
ISSN | Citations | PageRank |
1520-6149 | 6 | 0.55 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michel Sarkis | 1 | 86 | 11.76 |
| Klaus Diepold | 2 | 437 | 56.47 |
| Knut Hueper | 3 | 7 | 0.92 |