Name
Abstract | ||
|---|---|---|
This paper introduces a new method for learning and inferring sparse representations of depth (disparity) maps. The proposed algorithm relaxes the usual assumption of the stationary noise model in sparse coding. This enables learning from data corrupted with spatially varying noise or uncertainty, such as that obtained by laser range scanners or structured light depth cameras. Sparse representatio... |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/JSTSP.2011.2158063 | IEEE Journal of Selected Topics in Signal Processing |
Keywords | Field | DocType |
Noise,Dictionaries,Encoding,Inference algorithms,Stereo vision,Noise reduction,Optimization | Cut,Computer vision,Structured light,Pattern recognition,Markov random field,Neural coding,Stereopsis,Computer science,Time-of-flight camera,Artificial intelligence,Graphical model,Prior probability | Journal |
Volume | Issue | ISSN |
5 | 5 | 1932-4553 |
Citations | PageRank | References |
11 | 0.54 | 28 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivana Tosic | 1 | 80 | 11.83 |
| Bruno A. Olshausen | 2 | 493 | 66.79 |
| Benjamin J. Culpepper | 3 | 106 | 8.92 |