An Accurate Linear Method for 3D Line Reconstruction for Binocular or Multiple View Stereo Vision

Zhong, Liang; Qin, Junyou; Xia, Yang; Zhang, Xiaohu; Shang, Yang; Zhang, Hongliang; Yu, Qifeng

doi:10.3390/s21020658

Cited by 10 publications

(3 citation statements)

References 18 publications

(28 reference statements)

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“…Given a set of points [𝑋 𝑖 , 𝑌 𝑖 ] 𝑇 (i=1,2,... ) in 2D plane, Delaunay triangulation is to find a group of triangles [17], so that any circumcircle of a triangle does not contain points, corresponding to Voronoi polygons. The center of the circumcircle of a triangle is the vertex of the Voronoi polygon, and the edge of the Voronoi polygon is on the vertical line of the two points.…”

Section: Delaunay Triangulationmentioning

confidence: 99%

Research on Weighing of Concrete Aggregate Pile Based on Binocular Vision

Wang²,

Zhuang³

et al. 2022

IJCAI

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At present, the weighing process of concrete aggregate is cumbersome, and the weighing result has a large error. This paper proposes a method for measuring the weight of irregular bone stockpiles based on binocular vision. Firstly, based on the principle of binocular vision, the improved SMG stereo matching algorithm and OTSU threshold segmentation algorithm are used to calculate the 3D point cloud coordinates corresponding to the disparity map. Then, the 3D reconstruction of the aggregate pile and the calculation method of volume and mass are proposed. The results show that the method can accurately measure the aggregate pile weight, and the measurement error is less than 6%. The method can effectively reduce the operating cost of the concrete batching station and improve the measurement efficiency.Povzetek: Razvita je metoda strojnega vida, ki oceni težo betonskih kosov.

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Section: Delaunay Triangulationmentioning

confidence: 99%

Research on Weighing of Concrete Aggregate Pile Based on Binocular Vision

Wang²,

Zhuang³

et al. 2022

IJCAI

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“…Binocular or stereo vision, used in diverse areas like autonomous driving [1,2], robot navigation [3,4], 3D reconstruction [5][6][7], and industrial inspection [8,9], employs two identical cameras to capture two images of the same target from different vantage points. The disparity between these images enables 3D reconstruction and measurement, the accuracy of which is heavily dependent on the precision of the camera calibration and stereo matching methods, thus making these processes key research subjects in stereo vision.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Stereo Camera Calibration Strategy: Leveraging Latin Hypercube Sampling and 2k Full-Factorial Design of Experiment Methods

Hao,

Tai,

Tan

2023

Sensors

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This research aimed to optimize the camera calibration process by identifying the optimal distance and angle for capturing checkered board images, with a specific focus on understanding the factors that influence the reprojection error (ϵRP). The objective was to improve calibration efficiency by exploring the impacts of distance and orientation factors and the feasibility of independently manipulating these factors. The study employed Zhang’s camera calibration method, along with the 2k full-factorial analysis method and the Latin Hypercube Sampling (LHS) method, to identify the optimal calibration parameters. Three calibration methods were devised: calibration with distance factors (D, H, V), orientation factors (R, P, Y), and the combined two influential factors from both sets of factors. The calibration study was carried out with three different stereo cameras. The results indicate that D is the most influential factor, while H and V are nearly equally influential for method A; P and R are the two most influential orientation factors for method B. Compared to Zhang’s method alone, on average, methods A, B, and C reduce ϵRP by 25%, 24%, and 34%, respectively. However, method C requires about 10% more calibration images than methods A and B combined. For applications where lower value of ϵRP is required, method C is recommended. This study provides valuable insights into the factors affecting ϵRP in calibration processes. The proposed methods can be used to improve the calibration accuracy for stereo cameras for the applications in object detection and ranging. The findings expand our understanding of camera calibration, particularly the influence of distance and orientation factors, making significant contributions to camera calibration procedures.

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“…Stereo vision is an effective method that is widely used in various fields. In [ 21 ], a linear method was developed for 3D line reconstruction using stereo vision. Reconstruction becomes difficult when the number of corresponding points on the lines is limited.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Soil Surface Roughness Using Stereo Vision Approach

Azizi

Abbaspour‐Gilandeh

Mesri-Gundoshmian

et al. 2021

Sensors

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Soil roughness is one of the most challenging issues in the agricultural domain and plays a crucial role in soil quality. The objective of this research was to develop a computerized method based on stereo vision technique to estimate the roughness formed on the agricultural soils. Additionally, soil till quality was investigated by analyzing the height of plow layers. An image dataset was provided in the real conditions of the field. For determining the soil surface roughness, the elevation of clods obtained from tillage operations was computed using a depth map. This map was obtained by extracting and matching corresponding keypoints as super pixels of images. Regression equations and coefficients of determination between the measured and estimated values indicate that the proposed method has a strong potential for the estimation of soil shallow roughness as an important physical parameter in tillage operations. In addition, peak fitting of tilled layers was applied to the height profile to evaluate the till quality. The results of this suggest that the peak fitting is an effective method of judging tillage quality in the fields.

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An Accurate Linear Method for 3D Line Reconstruction for Binocular or Multiple View Stereo Vision

Cited by 10 publications

References 18 publications

Research on Weighing of Concrete Aggregate Pile Based on Binocular Vision

Research on Weighing of Concrete Aggregate Pile Based on Binocular Vision

A Systematic Stereo Camera Calibration Strategy: Leveraging Latin Hypercube Sampling and 2k Full-Factorial Design of Experiment Methods

Estimation of Soil Surface Roughness Using Stereo Vision Approach

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