DocumentCode
253879
Title
Light Field Stereo Matching Using Bilateral Statistics of Surface Cameras
Author
Can Chen ; Haiting Lin ; Zhan Yu ; Sing Bing Kang ; Jingyi Yu
Author_Institution
Univ. of Delaware, Newark, DE, USA
fYear
2014
fDate
23-28 June 2014
Firstpage
1518
Lastpage
1525
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.
Keywords
cameras; filtering theory; image matching; statistical analysis; stereo image processing; 3D point; angular radiance distribution; bilateral SCam analysis; bilateral consistency metric; bilateral statistics; consistency-disparity curves; edge preserving guided filter; light field stereo matching process; near occlusion boundaries; occlusions; surface cameras; Cameras; Image color analysis; Measurement; Reliability; Stereo vision; Surface texture; Three-dimensional displays; Bilateral Statistics; Light field stereo; Surface camera; occlusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
Conference_Location
Columbus, OH
Type
conf
DOI
10.1109/CVPR.2014.197
Filename
6909593
Link To Document