Paper Info
Title
Dependable dense stereo matching by both two-layer recurrent process and chaining search
Abstract
Disparity computation in occluded or texture-less regions is considered to be a fundamental issue in dense stereo matching, but there is another practical issue that must be resolved before it can be used effectively in various robotics applications. This issue is the problem of intensity difference between corresponding pixels of an image pair. To tackle such problems, we present a dependable stereo matching algorithm using two-layer recurrent process and chaining search. Two-layer process integrates pixel and region-levels information through recurrent interaction. To estimate the precise disparities in occluded regions, reliable disparities in non-occluded region are propagated to occluded regions by the proposed chaining search. To test our algorithm, it was compared with two outstanding algorithms in Middlebury benchmark using Gaussian noisy images. The results validated the effectiveness of our approach.
Year
DOI
Venue
2012
10.1109/IROS.2012.6386179
IROS
Keywords
Field
DocType
texture-less regions,image matching,occluded regions,robotics applications,gaussian noisy images,disparity computation,image pair pixel,gaussian processes,middlebury benchmark,dependable stereo matching algorithm,stereo image processing,two-layer recurrent process,image texture,pixel-level information,chaining search,region-level information,intensity difference,robot vision,image segmentation,psnr,robots,reliability,computational modeling,stereo vision
Template matching,Computer vision,Stereo cameras,Chaining,Image texture,Stereopsis,Computer science,Image segmentation,Artificial intelligence,Pixel,Computer stereo vision
Conference
ISSN
ISBN
Citations 
2153-0858
978-1-4673-1737-5
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
Sehyung Lee100.34
Youngbin Park245.85
Il Hong Suh3780110.60