scholarly journals Panoramic Stereo Imaging of a Bionic Compound-Eye Based on Binocular Vision

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1944
Author(s):  
Xinhua Wang ◽  
Dayu Li ◽  
Guang Zhang
Keyword(s):  
Real Time ◽  
Stereo Vision ◽  
Optimization Design ◽  
Stereo Matching ◽  
Depth Information ◽  
Stereo Imaging ◽  
Design Scheme ◽  
Panoramic Imaging ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

With the rapid development of the virtual reality industry, one of the bottlenecks is the scarcity of video resources. How to capture high-definition panoramic video with depth information and real-time stereo display has become a key technical problem to be solved. In this paper, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed. Combined with the real-time processing algorithm of multi detector mosaic panoramic stereo imaging image, a panoramic stereo real-time imaging system is developed. Firstly, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed, and the space coordinate calibration platform of ultra-high precision panoramic camera based on theodolite angle compensation function is constructed. The projection matrix of adjacent cameras is obtained by solving the imaging principle of binocular stereo vision. Then, a real-time registration algorithm of multi-detector mosaic image and Lucas-Kanade optical flow method based on image segmentation are proposed to realize stereo matching and depth information estimation of panoramic imaging, and the estimation results are analyzed effectively. Experimental results show that the stereo matching time of panoramic imaging is 30 ms, the registration accuracy is 0.1 pixel, the edge information of depth map is clearer, and it can meet the imaging requirements of different lighting conditions.

scholarly journals A Real-Time Range Finding System with Binocular Stereo Vision

10.5772/50921 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 26 ◽  
Author(s):  
Xiao-Bo Lai ◽  
Hai-Shun Wang ◽  
Yue-Hong Xu
Keyword(s):  
Real Time ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Single Point ◽  
Time Range ◽  
Real Time Control ◽  
Matching Algorithm ◽  
Range Finding ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To acquire range information for mobile robots, a TMS320DM642 DSP-based range finding system with binocular stereo vision is proposed. Firstly, paired images of the target are captured and a Gaussian filter, as well as improved Sobel kernels, are achieved. Secondly, a feature-based local stereo matching algorithm is performed so that the space location of the target can be determined. Finally, in order to improve the reliability and robustness of the stereo matching algorithm under complex conditions, the confidence filter and the left-right consistency filter are investigated to eliminate the mismatching points. In addition, the range finding algorithm is implemented in the DSP/BIOS operating system to gain real-time control. Experimental results show that the average accuracy of range finding is more than 99% for measuring single-point distances equal to 120cm in the simple scenario and the algorithm takes about 39ms for ranging a time in a complex scenario. The effectivity, as well as the feasibility, of the proposed range finding system are verified.

Object Tracking and Positioning Based on Stereo Vision

2013 ◽  
Vol 303-306 ◽  
pp. 313-317 ◽  
Author(s):  
Zhong Wei Zhou ◽  
Min Xu ◽  
Wei Fu ◽  
Ji Zeng Zhao
Keyword(s):  
Object Tracking ◽  
Real Time ◽  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Spatial Location ◽  
Binocular Stereo Vision ◽  
Camshift Algorithm ◽  
Spatial Location Information ◽  
Binocular Stereo

The goal of this paper is to present a method for object tracking and positioning based on stereo vision in real time. The method effectively combined stereo matching algorithm with object tracking algorithm, and calculated the spatial location information of the object by using binocular stereo vision while the object is being tracked. The stereo matching used dynamic programming, image pyramids and control points modification algorithm, and the object tracking mainly utilized CamShift algorithm in this paper. The experimental results have confirmed that the proposed method realized real-time tracking for moving object, accurate calculating for the object three-dimensional coordinates, which meet the applied needs of servo follow-up system.

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.

Baggage Specification Detection Based on the Binocular Vision

2013 ◽  
Vol 278-280 ◽  
pp. 861-865
Author(s):  
Qing Ji Gao ◽  
Lu Yang
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Detection Algorithm ◽  
Epipolar Constraint ◽  
Middle Point ◽  
Vision Measurement ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Stereo Vision Measurement

To the baggage specification automatically detection problem of self-service bag drop system, a baggage size detection algorithm based on stereo vision is proposed. The algorithm is based on binocular stereo vision measurement principle. Firstly, the canny edges of baggage image are extracted as the feature points. With the disparity gradient constraint and epipolar constraint, Stereo matching algorithm based on edge features is proposed, meanwhile, the two images play a symmetric role to ensure the reliability of matching in the matching process. The coordinates of the three dimensional points are derived with approximation of the middle point of the common perpendicular line in different planes. Experimental results show that the proposed algorithm can detect the baggage specification with appropriate accuracy.

3D Reconstruction Based on Binocular Stereo Vision of Robot

2011 ◽  
Vol 338 ◽  
pp. 645-648 ◽  
Author(s):  
Zhi Gang Niu ◽  
Li Jun Li ◽  
Tie Wang
Keyword(s):  
Stereo Vision ◽  
Coal Mine ◽  
Stereo Matching ◽  
Least Square Method ◽  
Least Square ◽  
Mine Detection ◽  
Binocular Stereo Vision ◽  
Harris Corner ◽  
Binocular Stereo ◽  
Projection Matrices

In order to meet the need of identifying obstacles and navigating for the Coal Mine Detection Robot which is used to rescue life and detect environment from coal mine disaster, binocular stereo vision is researched and 3D model of objects around the robot is reconstructed by means of two cameras of visual system built in the robot. The two cameras are calibrated and two projection matrices of them are obtained. Then, two images of the same scene are obtained by the two cameras. The matching points of two-dimensional coordinate are got through Harris corner extraction and stereo matching. According to the principle of binocular vision, equations are obtained and solved by least square method, which can calculated the discrete points of 3D coordinate.

Spatial Point Reconstruction Based on Binocular Stereo Vision

2014 ◽  
Vol 962-965 ◽  
pp. 2809-2813 ◽  
Author(s):  
Jie Yu ◽  
Yu Min Ge ◽  
Bao Shu Li ◽  
Shang Chen
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Robot Vision ◽  
Spatial Location ◽  
It Use ◽  
Spatial Point ◽  
Binocular Stereo Vision ◽  
Spatial Location Information ◽  
Binocular Stereo

Binocular stereo vision is an important branch of robot vision technology, it use two cameras in different position or a camera which can be move or rotate to shoot the same scene images, by calculating the parallax of spatial point in two images, get the spatial location information. There is a study based on the binocular stereo vision for three-dimensional spatial reconstruction, in view of the problem of vision image acquisition, camera calibration,stereo matching and 3d reconstruction in the binocular stereo application technology.

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