IEICE TRANSACTIONS on Information
Stereo Matching Using Local Plane Fitting in Confidence-Based Support Window
Summary :
This paper addresses stereo matching under scenarios of smooth region and obviously slant plane. We explore the flexible handling of color disparity, spatial relation and the reliability of matching pixels in support windows. Building upon these key ingredients, a robust stereo matching algorithm using local plane fitting by Confidence-based Support Window (CSW) is presented. For each CSW, only these pixels with high confidence are employed to estimate optimal disparity plane. Considering that RANSAC has shown to be robust in suppressing the disturbance resulting from outliers, we employ it to solve local plane fitting problem. Compared with the state of the art local methods in the computer vision community, our approach achieves the better performance and time efficiency on the Middlebury benchmark.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.2 pp.699-702
- Publication Date
- 2012/02/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.699
- Type of Manuscript
- LETTER
- Category
- Image Recognition, Computer Vision
Authors
Keyword
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Chenbo SHI, Guijin WANG, Xiaokang PEI, Bei HE, Xinggang LIN, "Stereo Matching Using Local Plane Fitting in Confidence-Based Support Window" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 2, pp. 699-702, February 2012, doi: 10.1587/transinf.E95.D.699.
Abstract: This paper addresses stereo matching under scenarios of smooth region and obviously slant plane. We explore the flexible handling of color disparity, spatial relation and the reliability of matching pixels in support windows. Building upon these key ingredients, a robust stereo matching algorithm using local plane fitting by Confidence-based Support Window (CSW) is presented. For each CSW, only these pixels with high confidence are employed to estimate optimal disparity plane. Considering that RANSAC has shown to be robust in suppressing the disturbance resulting from outliers, we employ it to solve local plane fitting problem. Compared with the state of the art local methods in the computer vision community, our approach achieves the better performance and time efficiency on the Middlebury benchmark.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.699/_p
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@ARTICLE{e95-d_2_699,
author={Chenbo SHI, Guijin WANG, Xiaokang PEI, Bei HE, Xinggang LIN, },
journal={IEICE TRANSACTIONS on Information},
title={Stereo Matching Using Local Plane Fitting in Confidence-Based Support Window},
year={2012},
volume={E95-D},
number={2},
pages={699-702},
abstract={This paper addresses stereo matching under scenarios of smooth region and obviously slant plane. We explore the flexible handling of color disparity, spatial relation and the reliability of matching pixels in support windows. Building upon these key ingredients, a robust stereo matching algorithm using local plane fitting by Confidence-based Support Window (CSW) is presented. For each CSW, only these pixels with high confidence are employed to estimate optimal disparity plane. Considering that RANSAC has shown to be robust in suppressing the disturbance resulting from outliers, we employ it to solve local plane fitting problem. Compared with the state of the art local methods in the computer vision community, our approach achieves the better performance and time efficiency on the Middlebury benchmark.},
keywords={},
doi={10.1587/transinf.E95.D.699},
ISSN={1745-1361},
month={February},}
Copy
TY - JOUR
TI - Stereo Matching Using Local Plane Fitting in Confidence-Based Support Window
T2 - IEICE TRANSACTIONS on Information
SP - 699
EP - 702
AU - Chenbo SHI
AU - Guijin WANG
AU - Xiaokang PEI
AU - Bei HE
AU - Xinggang LIN
PY - 2012
DO - 10.1587/transinf.E95.D.699
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2012
AB - This paper addresses stereo matching under scenarios of smooth region and obviously slant plane. We explore the flexible handling of color disparity, spatial relation and the reliability of matching pixels in support windows. Building upon these key ingredients, a robust stereo matching algorithm using local plane fitting by Confidence-based Support Window (CSW) is presented. For each CSW, only these pixels with high confidence are employed to estimate optimal disparity plane. Considering that RANSAC has shown to be robust in suppressing the disturbance resulting from outliers, we employ it to solve local plane fitting problem. Compared with the state of the art local methods in the computer vision community, our approach achieves the better performance and time efficiency on the Middlebury benchmark.
ER -
English
