SIA OpenIR  > 机器人学研究室
Alternative TitleRobust estimation method for dense disparity of binocular vision under textureless environment
杜英魁; 刘成; 田丹; 韩晓微; 原忠虎
Source Publication光学精密工程
Indexed ByEI ; CSCD
EI Accession number20172703864508
Contribution Rank2
Funding Organization辽宁省高等学校创新团队资助项目(LT2013024) ; 机器人学国家重点实验室开放基金资助项目(2015008) ; 辽宁省自然科学基金资助项目(2015020158) ; 辽宁省博士科研启动基金项目(201601213)
Keyword弱纹理环境 双目视觉 视差估计 置信度传播 参数空间投票
Other AbstractPrecise dense disparity estimation is the key for stereo visual system to recover three-dimensional information of observation scene. From practical application perspective of stereo vision in robot environment perception, a dense disparity figure estimation algorithm having good robustness, accuracy and processing speed to key influence factors (texturelessness, shadow and blocking etc.) was proposed. Aimed at texturelessness, shadow and uncontinuous, belief propagation algorithm based on gray-scale similarity probability had been designed to realize rapid and accurate estimation of initial value of disparity by combining with disparity smoothness constraint. The message vector defined by disparity class was propagated through anisotropic diffusion and parallel iteration. Message vector included energy information representing gray-scale similarity and smoothness of pixel point. Initial estimation of disparity could be gained rapidly through iteration convergence of global energy function. According to the priori knowledge that independent connected area generally had similar textural features and disparity conformance, parameter space voting self-adaption disparity approximation surface estimation algorithm on the basis of Mean-Shift clustering partitioning algorithm was proposed to perform fine optimization estimation of dense disparity. 5 groups of standard test image having different textureless features, 4 groups of actual image under indoor environment, 4 groups of actual image under outdoor environment and 4 groups of actual environment image under special lighting environment through selenographic simulation were utilized to perform test experiment and experimental result shows that the proposed algorithm has good robustness and effectiveness. © 2017, Science Press.
Citation statistics
Cited Times:1[CSCD]   [CSCD Record]
Document Type期刊论文
Corresponding Author杜英魁
Recommended Citation
GB/T 7714
杜英魁,刘成,田丹,等. 弱纹理环境双目视觉稠密视差鲁棒估计方法[J]. 光学精密工程,2017,25(4):554-562.
APA 杜英魁,刘成,田丹,韩晓微,&原忠虎.(2017).弱纹理环境双目视觉稠密视差鲁棒估计方法.光学精密工程,25(4),554-562.
MLA 杜英魁,et al."弱纹理环境双目视觉稠密视差鲁棒估计方法".光学精密工程 25.4(2017):554-562.
Files in This Item:
File Name/Size DocType Version Access License
弱纹理环境双目视觉稠密视差鲁棒估计方法.(614KB)期刊论文作者接受稿开放获取ODC PDDLView Application Full Text
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[杜英魁]'s Articles
[刘成]'s Articles
[田丹]'s Articles
Baidu academic
Similar articles in Baidu academic
[杜英魁]'s Articles
[刘成]'s Articles
[田丹]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[杜英魁]'s Articles
[刘成]'s Articles
[田丹]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 弱纹理环境双目视觉稠密视差鲁棒估计方法.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.