Name
Title | ||
|---|---|---|
A Novel Relative Camera Motion Estimation Algorithm with Applications to Visual Odometry |
Abstract | ||
|---|---|---|
In this paper, we propose a novel method to estimate the relative camera motions of three consecutive images. Given a set of point correspondences in three views, the proposed method determines the fundamental matrix representing the geometrical relationship between the first two views by using the eight-point algorithm. Then, by minimizing the proposed cost function with the fundamental matrix, the relative camera motions over three views are precisely estimated. The experimental results show that the proposed method outperforms the conventional two-view and three-view geometry-based method in terms of the accuracy. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISM.2018.000-4 | 2018 IEEE International Symposium on Multimedia (ISM) |
Keywords | Field | DocType |
visual odometry,eight-point algorithm,trifocal tensor | Computer vision,Eight-point algorithm,Pattern recognition,Visual odometry,Computer science,Artificial intelligence,Statistical classification,Motion estimation algorithm,Fundamental matrix (computer vision),Trifocal tensor | Conference |
ISBN | Citations | PageRank |
978-1-5386-6858-0 | 0 | 0.34 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yue Jiang | 1 | 0 | 0.34 |
| muncheon kang | 2 | 26 | 6.79 |
| Ming Fan | 3 | 83 | 10.32 |
| sungho chae | 4 | 14 | 3.75 |
| Sung-Jea Ko | 5 | 1051 | 114.34 |