Name
Abstract | ||
|---|---|---|
We present a highly efficient method for estimating the structure and motion from image sequences taken by uncalibrated cameras. The basic principle is to do projective reconstruction first followed by Euclidean upgrading. However, the projective reconstruction step dominates the total computational time, because we need to solve eigenproblems of matrices whose size depends on the number of frames or feature points. In this paper, we present a new algorithm that yields the same solution using only matrices of constant size irrespective of the number of frames or points. We demonstrate the superior performance of our algorithm, using synthetic and real video images. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-78157-8_12 | RobVis |
Keywords | Field | DocType |
euclidean upgrading,feature point,basic principle,iterative low complexity factorization,efficient method,real video image,new algorithm,constant size,projective reconstruction step,superior performance,projective reconstruction | Discrete mathematics,Matrix (mathematics),Algorithm,Projective reconstruction,Factorization,Euclidean geometry,Real projective line,Mathematics | Conference |
Volume | ISSN | ISBN |
4931 | 0302-9743 | 3-540-78156-0 |
Citations | PageRank | References |
1 | 0.35 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanno Ackermann | 1 | 57 | 11.29 |
| Kenichi Kanatani | 2 | 1468 | 320.07 |