AGO: Accelerating Global Optimization for Accurate Stereo Matching

2018 ◽  
pp. 67-80 ◽  
Author(s):  
Peng Yao ◽  
Hua Zhang ◽  
Yanbing Xue ◽  
Shengyong Chen
Keyword(s):  
Global Optimization ◽  
Stereo Matching

Stereo Matching Algorithm Based on Belief Propagation System

2015 ◽  
Vol 713-715 ◽  
pp. 1931-1934
Author(s):  
Si Chen Pan
Keyword(s):  
Computer Vision ◽  
Global Optimization ◽  
Information Transmission ◽  
Optimization Algorithm ◽  
Stereo Matching ◽  
Belief Propagation ◽  
Global Optimization Algorithm ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Stereo Reconstruction

Stereo matching methods are widely used in computer vision and stereo reconstruction, from the perspective of improving the matching accuracy, this paper focuses on the global optimization algorithm. An improved Belief Propagation method is proposed in this paper, by involving more pixels into information transmission, our method improves the accuracy ofstereo matching. The experimental results verify the efficiencyand reliability of our method.

scholarly journals Selective Segmentation for Global Optimization of Depth Estimation in Complex Scenes

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Sheng Liu ◽  
Haiqiang Jin ◽  
Xiaojun Mao ◽  
Binbin Zhai ◽  
Ye Zhan ◽  
...  
Keyword(s):  
Global Optimization ◽  
Stereo Matching ◽  
Cost Optimization ◽  
Depth Estimation ◽  
Optimization Method ◽  
Optimization Approach ◽  
Real Scene ◽  
Complex Scenes ◽  
Matching Cost ◽  
Image Pairs

This paper proposes a segmentation-based global optimization method for depth estimation. Firstly, for obtaining accurate matching cost, the original local stereo matching approach based on self-adapting matching window is integrated with two matching cost optimization strategies aiming at handling both borders and occlusion regions. Secondly, we employ a comprehensive smooth term to satisfy diverse smoothness request in real scene. Thirdly, a selective segmentation term is used for enforcing the plane trend constraints selectively on the corresponding segments to further improve the accuracy of depth results from object level. Experiments on the Middlebury image pairs show that the proposed global optimization approach is considerably competitive with other state-of-the-art matching approaches.

Global Optimization

1993 ◽  
Author(s):  
Reiner Horst ◽  
Hoang Tuy
Keyword(s):  
Global Optimization

Probability Models in Global Optimization

Informatica ◽  
2016 ◽  
Vol 27 (2) ◽  
pp. 323-334 ◽  
Author(s):  
James M. Calvin
Keyword(s):  
Global Optimization ◽  
Probability Models
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