Name
Abstract | ||
|---|---|---|
Several factorization techniques have been proposed for tackling the Structure from Motion problem. Most of them provide a good solution, while the amount of missing data is within an acceptable ratio. Focussing on this problem, we propose an incremental multiresolution scheme able to deal with a high rate of missing data, as well as noisy data. It is based on an iterative approach that applies a classical factorization technique in an incrementally reduced space. Information recovered following a coarse-to-fine strategy is used for both, filling in the missing entries of the input matrix and denoising original data. A statistical study of the proposed scheme compared to a classical factorization technique is given. Experimental results obtained with synthetic data and real video sequences are presented to demonstrate the viability of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11758501_75 | International Conference on Computational Science (1) |
Keywords | Field | DocType |
original data,proposed scheme,factorization technique,noisy data,classical factorization technique,missing entry,missing data,synthetic data,motion problem,structure from motion | Structure from motion,Matrix (mathematics),Iterative method,Computer science,Signal-to-noise ratio,Algorithm,Multiresolution analysis,Synthetic data,Factorization,Missing data | Conference |
Volume | ISSN | ISBN |
3991 | 0302-9743 | 3-540-34379-2 |
Citations | PageRank | References |
4 | 0.44 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carme Julià | 1 | 58 | 6.78 |
| Angel Sappa | 2 | 16 | 2.00 |
| Felipe Lumbreras | 3 | 328 | 28.04 |
| Joan Serrat | 4 | 1262 | 103.04 |
| Antonio López | 5 | 104 | 9.02 |