Dependable dense stereo matching by both two-layer recurrent process and chaining search

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Sehyung Lee, Youngbin Park, Il Hong Suh
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
Educational institutions
Image segmentation
PSNR
Reliability
Robots
Stereo vision
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2153-0858
2153-0866
DOI:10.1109/IROS.2012.6386179