Name
Abstract | ||
|---|---|---|
In this paper, we propose a novel photometric stereo method that uses singular value decomposition. Singular value decomposition can solve the photometric stereo problem when the light source direction is unknown; however, it has the critical problem of being sensitive to outliers. We therefore propose a novel singular value decomposition method that is robust to outliers. We also show some results of our photometric stereo method when applied to objects that involve not only diffuse reflection but also specular reflection. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICIP.2010.5650067 | Image Processing |
Keywords | Field | DocType |
photometric light sources,singular value decomposition,stereo image processing,SVD,light sources,missing data,photometric stereo,singular value decomposition | Singular value decomposition,Computer vision,Pattern recognition,Stereopsis,Computer science,Specular reflection,Diffuse reflection,Robustness (computer science),Pixel,Artificial intelligence,Missing data,Photometric stereo | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-7993-1 | 978-1-4244-7993-1 | 12 |
PageRank | References | Authors |
0.57 | 10 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daisuke Miyazaki | 1 | 175 | 9.33 |
| Katsushi Ikeuchi | 2 | 4651 | 881.49 |