Name
Abstract | ||
|---|---|---|
The power of Markov random field formulations of lowlevel vision problems, such as stereo, has been known for some time. However, recent advances, both algorithmic and in processing power, have made their application practical. This paper presents a novel implementation of Bayesian belief propagation for graphics processing units found in most modern desktop and notebook computers, and applies it to the stereo problem. The stereo problem is used for comparison to other BP algorithms. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/CRV.2006.19 | CRV |
Keywords | Field | DocType |
stereo problem,notebook computer,belief propagation,bp algorithm,image-based rendering,markov random field formulation,modern desktop,recent advance,stereo vision,novel implementation,lowlevel vision problem,bayesian belief propagation,graphics processing unit.,processing power,information technology,computer vision,computer graphics,belief,layout,pixel,propagation,image based rendering,random variables | Graphics,Stereo cameras,Computer vision,Computer graphics (images),Stereopsis,Markov random field,Computer science,Artificial intelligence,Shader,Image-based modeling and rendering,Graphics processing unit,Belief propagation | Conference |
ISBN | Citations | PageRank |
0-7695-2542-3 | 29 | 1.55 |
References | Authors | |
12 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alan Brunton | 1 | 30 | 1.91 |
| Chang Shu | 2 | 265 | 20.50 |
| Gerhard Roth | 3 | 264 | 16.52 |