Name
Abstract | ||
|---|---|---|
In this paper, we introduce a bilateral consistency metric on the surface camera (SCam) [26] for light field stereo matching to handle significant occlusions. The concept of SCam is used to model angular radiance distribution with respect to a 3D point. Our bilateral consistency metric is used to indicate the probability of occlusions by analyzing the SCams. We further show how to distinguish between on-surface and free space, textured and non-textured, and Lambertian and specular through bilateral SCam analysis. To speed up the matching process, we apply the edge preserving guided filter [14] on the consistency-disparity curves. Experimental results show that our technique outperforms both the state-of-the-art and the recent light field stereo matching methods, especially near occlusion boundaries. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CVPR.2014.197 | CVPR |
Keywords | Field | DocType |
consistency-disparity curves,image matching,angular radiance distribution,statistical analysis,occlusions,light field stereo matching process,surface camera,bilateral statistics,bilateral consistency metric,cameras,filtering theory,light field stereo,near occlusion boundaries,stereo image processing,edge preserving guided filter,occlusion,surface cameras,3d point,bilateral scam analysis,light field stereo, bilateral statistics, surface camera, occlusion,measurement,reliability,surface texture,stereo vision | Stereo matching,Computer vision,Stereo camera,Pattern recognition,Computer science,Specular reflection,Light field,Free space,Artificial intelligence,Radiance,Speedup,Computer stereo vision | Conference |
ISSN | Citations | PageRank |
1063-6919 | 40 | 1.25 |
References | Authors | |
19 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Can Chen | 1 | 83 | 8.27 |
| Haiting Lin | 2 | 85 | 5.05 |
| Zhan Yu | 3 | 122 | 7.17 |
| Sing Bing Kang | 4 | 5064 | 345.13 |
| Jingyi Yu | 5 | 1238 | 101.25 |