3D pose estimation of large and complicated workpieces based on binocular stereo vision

2017 ◽  
Vol 56 (24) ◽  
pp. 6822 ◽  
Author(s):  
Zhifeng Luo ◽  
Ke Zhang ◽  
Zhigang Wang ◽  
Jian Zheng ◽  
Yixin Chen
Keyword(s):  
Pose Estimation ◽  
Stereo Vision ◽  
3D Pose Estimation ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

Circle Pose Estimation Based on Stereo Vision

2012 ◽  
Vol 263-266 ◽  
pp. 2408-2413 ◽  
Author(s):  
Wen Juan Ma ◽  
Shu Sen Sun ◽  
Jin Yu Song ◽  
Wen Shu Li
Keyword(s):  
Pose Estimation ◽  
Stereo Vision ◽  
Closed Form Solution ◽  
Simulated Data ◽  
Real Data ◽  
Form Solution ◽  
Perspective View ◽  
Simple Method ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

This paper presents a simple method of circle pose estimation based on binocular stereo vision. It takes the projective equation of a circle as the basis, and gives the closed form solution of the pose parameters. Since there are two possible sets of pose parameters for a circle from one calibrated perspective view, the stereo vision constraints are incorporated and the accurate pose parameters are determined. Experiments using computer simulated data and real data demonstrate the robustness and accuracy of our method.

scholarly journals High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Target Localization ◽  
Parallel Structure ◽  
Moving Target ◽  
Target Area ◽  
Moving Targets ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

Bubble behavior characteristics based on virtual binocular stereo vision

2018 ◽  
Vol 14 (1) ◽  
pp. 44-47 ◽  
Author(s):  
Ting Xue ◽  
Ling-shuang Xu ◽  
Shang-zhen Zhang
Keyword(s):  
Stereo Vision ◽  
Bubble Behavior ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Behavior Characteristics

Binocular Stereo Vision Based Illuminance Measurement Used for Intelligent Lighting with LED

Optik ◽  
2021 ◽  
pp. 166651
Author(s):  
Lianghui Li ◽  
Jiachen Wang ◽  
Shengli Yang ◽  
Hao Gong
Keyword(s):  
Stereo Vision ◽  
Binocular Stereo Vision ◽  
Binocular Stereo
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