Vision-Based Aerial Refueling Docking Based on SURF Algorithm

2011 ◽  
Vol 130-134 ◽  
pp. 3102-3106
Author(s):  
Si Yuan Qin ◽  
Jian Guo Yan
Keyword(s):  
Vision System ◽  
Three Dimensional ◽  
Spatial Position ◽  
Target Point ◽  
Feature Points ◽  
Aerial Refueling ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Left And Right

For the Boom and Receptacle Air Refueling, in order to locate the spatial position of the refueling receptacle, an object locating method is developed based on Speeded-up Robust Feature (SURF) algorithm. Firstly, SURF feature vector matching algorithm is used to detect and collect suitable SURF feature points in left and right images produced by binocular stereo vision system separately. Then the point that shows the same spatial position in both left and right images can be located through process such as deleting wrong matching points and calculating the image coordinate of the target point. Finally, the three-dimensional coordinates of the target points could be rebuilt in the camera’s coordinate system. According to the results of experiments, this method has good robustness and practicability.

scholarly journals Stereo Matching Based on Immune Neural Network in Abdomen Reconstruction

2015 ◽  
Vol 2015 ◽  
pp. 1-15
Author(s):  
Huan Liu ◽  
Kuangrong Hao ◽  
Yongsheng Ding ◽  
Chunjuan Ouyang
Keyword(s):  
Neural Network ◽  
Stereo Matching ◽  
Feature Matching ◽  
Three Dimensional ◽  
Target Point ◽  
Feature Points ◽  
Matching Algorithm ◽  
Optimization Task ◽  
Feasible Alternative ◽  
Single Neural Network

Stereo feature matching is a technique that finds an optimal match in two images from the same entity in the three-dimensional world. The stereo correspondence problem is formulated as an optimization task where an energy function, which represents the constraints on the solution, is to be minimized. A novel intelligent biological network (Bio-Net), which involves the human B-T cells immune system into neural network, is proposed in this study in order to learn the robust relationship between the input feature points and the output matched points. A model from input-output data (left reference point-right target point) is established. In the experiments, the abdomen reconstructions for different-shape mannequins are then performed by means of the proposed method. The final results are compared and analyzed, which demonstrate that the proposed approach greatly outperforms the single neural network and the conventional matching algorithm in precise. Particularly, as far as time cost and efficiency, the proposed method exhibits its significant promising and potential for improvement. Hence, it is entirely considered as an effective and feasible alternative option for stereo matching.

The Calibration of Binocular Stereo Vision for the Camera Based on Machine Vision Measurement

2014 ◽  
Vol 701-702 ◽  
pp. 361-366
Author(s):  
Xiao Jing Yang ◽  
Si Qi Wang
Keyword(s):  
Machine Vision ◽  
Camera Calibration ◽  
Stereo Vision ◽  
Vision System ◽  
Calibration Target ◽  
Vision Measurement ◽  
Matlab Program ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Left And Right

Camera calibration is the most important stage of machine vision measurement. The principle and method of camera calibration for binocular stereo vision system are introduced and the left and right CCD are respectively calibrated by using the prepared calibration target and the MATLAB program. Then internal and external camera parameters are obtained by the calibration experiments. The experimental results show that the calibration results have high precision.

Research of Stereo Matching Based on HALCON

2013 ◽  
Vol 415 ◽  
pp. 361-364
Author(s):  
Hui Yu Xiang ◽  
Zhe Li ◽  
Jia Jun Huang ◽  
Baoan Han
Keyword(s):  
Image Matching ◽  
Stereo Matching ◽  
Vision System ◽  
Difficult Problem ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Matching Window

Binocular stereo matching is a hot and difficult problem in machine vision. In this paper, based on the matching method of Halcon which is visual software perform image matching. First, performing binocular stereo vision system calibration, based on the calibration results acquired the epipolar standard geometric structure. Then, image matching researched under this structure. At last, using ncc matching algorithm, through comparing the different parameters matching window obtain ideal match results. Experiments prove that this method not only can effectively shorten matching time, but also can achieve higher matching accuracy.

scholarly journals Pose Estimation under Visual Sensing Technology and Its Application in Art Design

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Bing Song ◽  
Meng Li ◽  
Liping Lou
Keyword(s):  
Pose Estimation ◽  
Vision System ◽  
Three Dimensional ◽  
Human Motion ◽  
Environmental Art ◽  
Visual Sensing ◽  
Sensing Technology ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Art Design

The study is aimed at solving the problem of large measurement errors caused by the binocular camera in traditional 3D art design, which leads to inaccurate 3D information of the target. The contour information extraction in the process of human motion pose reconstruction is easily affected by the noise in the image. Therefore, a binocular stereo vision system is built first and it integrates image acquisition, camera calibration, and image processing. The dedistortion method is used to process the image because it can reduce errors. Second, a three-dimensional human motion pose reconstruction model is implemented, the Gaussian template is used to remove the noise in the image frame, and the change detection template (CDM) is used to solve the problem of background “exposure” and “occlusion.” Finally, simulation experiments are designed to verify the system and model designed. Since the research on the application of pose estimation based on visual sensing technology in art design is still blank, such research has great significance and provides a reference for the research in the field. The literature analysis is used to expound and analyze the application of pose estimation based on visual sensing technology in visual communication design and environmental art design: (1) although the binocular stereo vision system causes some errors in the measurement, the overall error is controlled within 2% and the accuracy is high, which proves that it can be applied to the acquisition of three-dimensional information of the target in art design; (2) there is a high degree of fitting between the video sequence data created by the three-dimensional human motion pose reconstruction model designed and the real motion data, which indicates that this method has high accuracy in processing image sequences and the feasibility of applying it to human pose reconstruction in three-dimensional art design is high; (3) through the analysis of the existing literature, it is found that most of the current visual-based attitude assessment studies are carried out by using network cameras combined with computers, and the quality of the obtained images is low. The combination of binocular stereo sensor and attitude estimation technology can be applied to the design of advertising, animation, games, and packaging, making the behavior of virtual characters in animation and games more vivid. The combination provides convenience for the collection of environmental spatial information and object attitude information, the formulation of a design scheme, and real-time monitoring of construction in environmental art design. The purpose of this study is to provide an important theoretical basis for the technical upgrading of art design.

System Design of Crane Robot Based on Binocular Stereo Vision

2013 ◽  
Vol 303-306 ◽  
pp. 1691-1694
Author(s):  
Zhi Kun Chen ◽  
Hong Yan Wang ◽  
Wen Hui Wang ◽  
Fu Bin Wang
Keyword(s):  
Stereo Vision ◽  
Production Efficiency ◽  
High Efficiency ◽  
Vision System ◽  
Three Dimensional ◽  
System Structure ◽  
Mature Stage ◽  
Security Risks ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

In order to improve the safety, high efficiency and stability in the process of the crane hoisting, this paper applied binocular stereo vision technology which has developed into a rather mature stage recently. Binocular stereo vision system could efficiently identify and accurately position various targets, so that it could decrease the crane driver’s working intensity, reduce security risks and improve the production efficiency. In order to experiments was convenient, developing the crane robot system could simulate the processes of crane work, establishing the relevant system structure model for the motion. According to the three-dimensional measuring principle of binocular stereo vision, this paper is proposed to identify and position for the targets, and experimental results show the error is ±10mm.

Research on Cotton Row Detection Algorithm Based on Binocular Vision

2014 ◽  
Vol 670-671 ◽  
pp. 1222-1227 ◽  
Author(s):  
Zhong Xiang Zhu ◽  
Yan He ◽  
Zhi Qiang Zhai ◽  
Jin Yi Liu ◽  
En Rong Mao
Keyword(s):  
Stereo Vision ◽  
Vision System ◽  
Three Dimensional ◽  
Measuring Method ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Depth Information ◽  
Automatic Navigation ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

As a relative locating method, machine vision is generally used for automatic navigation of cotton cultivator or cotton insecticide sprayer. However, it is difficult to achieve reliable and stable recognition of crop row with monocular stereo vision system, because it neither can access directly to the depth information of the image, which leads to massive time-consuming calculation, nor possess high-accuracy recognition or a good anti-noise property. This paper presents an algorithm for cotton row detection based on binocular stereo vision to be used for automatic navigation of cotton cultivator. The Zhang's plane calibration is used to obtain the internal and external parameters of the binocular stereo vision. Preprocessing means are applied to distinguish the cotton from soil, stereoscopic match is conducted according to the SIFT operators after the preprocessing of images, after which cotton space three-dimensional coordinates are acquired by parallax distance measuring method, with the elevation information combination of Hough transform, cotton lines are finally detected. The detection results indicate that this method has an accuracy higher than 90%, which primarily meets the need of automatic navigation for cotton cultivator.

Camera Calibration Based Multi-Objects Location in Binocular Stereo Vision

2015 ◽  
Vol 719-720 ◽  
pp. 1217-1222 ◽  
Author(s):  
Ying Zhu ◽  
Long Ye ◽  
Jing Ling Wang ◽  
Qin Zhang
Keyword(s):  
Camera Calibration ◽  
Three Dimensional ◽  
Mathematical Methods ◽  
3D Space ◽  
Binocular Stereo Vision ◽  
Extrinsic Parameters ◽  
Binocular Stereo ◽  
Left And Right ◽  
Three Dimensional Coordinate ◽  
Intrinsic And Extrinsic Parameters

In order to capture high quality binocular stereo video, it is necessary to manipulate both the convergence and the interaxial to take control of the depth of objects within the 3D space. Therefore the scene understanding becomes important as it can increase the efficiency of parameters control. In this paper, a camera calibration based multi-objects location method is introduced with the motivation that supply prior information of adjusting the convergence and the interaxial during capturing. Firstly, we are intended to calibrate the two cameras to get the intrinsic and extrinsic parameters. And then, we select points of the object in the images taken by left and right cameras respectively to determine its locations in the two images. With three-dimensional coordinate of objects, the distance between the object and camera baseline is calculated by mathematical methods.

Distance Measurement Algorithm Based on Binocular Stereo Vision

2014 ◽  
Vol 635-637 ◽  
pp. 948-952 ◽  
Author(s):  
Hui Min Long ◽  
Hai Yan Guo ◽  
Feng Liang ◽  
Gui Hua Liu
Keyword(s):  
Stereo Vision ◽  
Three Dimensional ◽  
Distance Measurement ◽  
Measurement Technology ◽  
Feature Points ◽  
Practical Applications ◽  
Binocular Stereo Vision ◽  
Dense Matching ◽  
Wide Range ◽  
Binocular Stereo

Distance measurement technology of binocular stereo vision has the advantages of wide-range detection, simplicity and reliability. The method is widely applied to robot obstacle avoidance and path planning. Binocular stereo vision can only measure the distance of images feature points generally. However, more information about distance of non-feature points is also needed to acquire in practical applications. This paper proposes a stereo distance measurement method, which can measure distance of points whether it is a feature point or not based on a dense matching method. A dense parallax map is obtained by the graph-cuts algorithm. On the basis of the calibration parameters of binocular camera and the left and right image dense parallax map, the three-dimensional coordinates of the any points and their distance will be gotten. The true image experiment has proved the feasibility of this algorithm with high accuracy and maneuverability.

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