scholarly journals VIDEOGRAMMETRIC RECONSTRUCTION APPLIED TO VOLCANOLOGY: PERSPECTIVES FOR A NEW MEASUREMENT TECHNIQUE IN VOLCANO MONITORING

2011 ◽  
Vol 21 (1) ◽  
pp. 31 ◽  
Author(s):  
Emmanuelle Cecchi ◽  
Jean Marc Lavest ◽  
Benjamin Van Wyk De Vries
Keyword(s):  
Spatial Location ◽  
Calibration Method ◽  
Reconstruction Method ◽  
Reconstruction Accuracy ◽  
Calibration Target ◽  
Analogue Model ◽  
Reconstruction Process ◽  
Internal Parameters ◽  
Initial Stage ◽  
View Reconstruction

This article deals with videogrammetric reconstruction of volcanic structures. As a first step, the method is tested in laboratory. The objective is to reconstruct small sand and plaster cones, analogous to volcanoes, that deform with time. The initial stage consists in modelling the sensor (internal parameters) and calculating its orientation and position in space, using a multi-view calibration method. In practice two sets of views are taken: a first one around a calibration target and a second one around the studied object. Both sets are combined in the calibration software to simultaneously compute the internal parameters modelling the sensor, and the external parameters giving the spatial location of each view around the cone. Following this first stage, a N-view reconstruction process is carried out. The principle is as follows: an initial 3D model of the cone is created and then iteratively deformed to fit the real object. The deformation of the meshed model is based on a texture coherence criterion. At present, this reconstruction method and its precision are being validated at laboratory scale. The objective will be then to follow analogue model deformation with time using successive reconstructions. In the future, the method will be applied to real volcanic structures. Modifications of the initial code will certainly be required, however excellent reconstruction accuracy, valuable simplicity and flexibility of the technique are expected, compared to classic stereophotogrammetric techniques used in volcanology.

Study on the Scanning Entity Reconstruction Method of RP Reverse Engineering

2012 ◽  
Vol 472-475 ◽  
pp. 1782-1786
Author(s):  
Qi Zhang ◽  
Hui Qun Zhou ◽  
Jing Yang ◽  
Xiu Ting Wang
Keyword(s):  
Reverse Engineering ◽  
Reference Point ◽  
Partial Information ◽  
Reconstruction Method ◽  
Alignment Method ◽  
Reconstruction Process ◽  
Reverse Process ◽  
Process System ◽  
View Reconstruction

In the multi-view reconstruction process, the paper unifies more partial information into one by using the three-reference-point alignment method. With the research on the process of image extraction, the method can improve the quality of the reconstruction data. The paper uses software CATIA as the platform to create the reverse process system of the product images which validate the feasibility of this method.

scholarly journals Constrained Multiple Planar Reconstruction for Automatic Camera Calibration of Intelligent Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4643
Author(s):  
Sang Jun Lee ◽  
Jeawoo Lee ◽  
Wonju Lee ◽  
Cheolhun Jang
Keyword(s):  
Camera Calibration ◽  
Calibration Method ◽  
Image Features ◽  
Intelligent Vehicles ◽  
Point Problem ◽  
Reconstruction Method ◽  
Calibration Methods ◽  
The World ◽  
Extrinsic Parameters ◽  
Automatic Camera Calibration

In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.

scholarly journals Reconstructing intragranular strain fields in polycrystalline materials from scanning 3DXRD data

2020 ◽  
Vol 53 (2) ◽  
pp. 314-325 ◽  
Author(s):  
N. Axel Henningsson ◽  
Stephen A. Hall ◽  
Jonathan P. Wright ◽  
Johan Hektor
Keyword(s):  
Three Dimensional ◽  
Polycrystalline Materials ◽  
Reconstruction Method ◽  
X Ray Diffraction ◽  
Reconstruction Accuracy ◽  
Strain Fields ◽  
Spatial Properties ◽  
Reconstruction Methods ◽  
Reconstruction Quality ◽  
Made In

Two methods for reconstructing intragranular strain fields are developed for scanning three-dimensional X-ray diffraction (3DXRD). The methods are compared with a third approach where voxels are reconstructed independently of their neighbours [Hayashi, Setoyama & Seno (2017). Mater. Sci. Forum, 905, 157–164]. The 3D strain field of a tin grain, located within a sample of approximately 70 grains, is analysed and compared across reconstruction methods. Implicit assumptions of sub-problem independence, made in the independent voxel reconstruction method, are demonstrated to introduce bias and reduce reconstruction accuracy. It is verified that the two proposed methods remedy these problems by taking the spatial properties of the inverse problem into account. Improvements in reconstruction quality achieved by the two proposed methods are further supported by reconstructions using synthetic diffraction data.

scholarly journals Refractive Two-View Reconstruction for Underwater 3D Vision

2019 ◽  
Vol 128 (5) ◽  
pp. 1101-1117 ◽  
Author(s):  
François Chadebecq ◽  
Francisco Vasconcelos ◽  
René Lacher ◽  
Efthymios Maneas ◽  
Adrien Desjardins ◽  
...  
Keyword(s):  
Structure From Motion ◽  
Real Data ◽  
Reconstruction Method ◽  
Underwater Imaging ◽  
Shape Estimation ◽  
Camera Model ◽  
Projection Model ◽  
3D Vision ◽  
Object Distance ◽  
View Reconstruction

AbstractRecovering 3D geometry from cameras in underwater applications involves the Refractive Structure-from-Motion problem where the non-linear distortion of light induced by a change of medium density invalidates the single viewpoint assumption. The pinhole-plus-distortion camera projection model suffers from a systematic geometric bias since refractive distortion depends on object distance. This leads to inaccurate camera pose and 3D shape estimation. To account for refraction, it is possible to use the axial camera model or to explicitly consider one or multiple parallel refractive interfaces whose orientations and positions with respect to the camera can be calibrated. Although it has been demonstrated that the refractive camera model is well-suited for underwater imaging, Refractive Structure-from-Motion remains particularly difficult to use in practice when considering the seldom studied case of a camera with a flat refractive interface. Our method applies to the case of underwater imaging systems whose entrance lens is in direct contact with the external medium. By adopting the refractive camera model, we provide a succinct derivation and expression for the refractive fundamental matrix and use this as the basis for a novel two-view reconstruction method for underwater imaging. For validation we use synthetic data to show the numerical properties of our method and we provide results on real data to demonstrate its practical application within laboratory settings and for medical applications in fluid-immersed endoscopy. We demonstrate our approach outperforms classic two-view Structure-from-Motion method relying on the pinhole-plus-distortion camera model.

scholarly journals Flexible method for accurate calibration of large-scale vision metrology system based on virtual 3-D targets and laser tracker

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989351
Author(s):  
Xi Zhang ◽  
Yuanzhi Xu ◽  
Haichao Li ◽  
Lijing Zhu ◽  
Xin Wang ◽  
...  
Keyword(s):  
High Precision ◽  
Stereo Vision ◽  
Large Scale ◽  
Vision System ◽  
Calibration Method ◽  
Field Of View ◽  
Large Field ◽  
Laser Tracker ◽  
Calibration Target ◽  
Pose Tracking

For the purpose of obtaining high-precision in stereo vision calibration, a large-size precise calibration target, which can cover more than half of the field of view is vital. However, large-scale calibration targets are very difficult to fabricate. Based on the idea of error tracing, a high-precision calibration method for vision system with large field of view by constructing a virtual 3-D calibration target with a laser tracker was proposed in this article. A virtual 3-D calibration target that covers the whole measurement space can be established flexibly and the measurement precision of the vision system can be traceable to the laser tracker. First, virtual 3-D targets by calculating rigid body transformation with unit quaternion method were constructed. Then, the high-order distortion camera model was taken into consideration. Besides, the calibration parameters were solved with Levenberg–Marquardt optimization algorithm. In the experiment, a binocular stereo vision system with the field of view of 4 × 3 × 2 m3 was built for verifying the validity and precision of the proposed calibration method. It is measured that the accuracy with the proposed method can be greatly improved comparing with traditional plane calibration method. The method can be widely used in industrial applications, such as in the field of calibrating large-scale vision-based coordinate metrology, and six-degrees of freedom pose tracking system for dimensional measurement of workpiece, as well as robotics geometrical accuracy detection and compensation.

scholarly journals SAR Observation Error Estimation Based on Maximum Relative Projection Matching

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Y. Zhang ◽  
B. P. Wang ◽  
Y. Fang ◽  
Z. X. Song
Keyword(s):  
Error Estimation ◽  
Estimation Method ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Reconstruction Method ◽  
Observation Error ◽  
Estimation Model ◽  
Reconstruction Process ◽  
Single Observation ◽  
Imaging Results

The existing sparse imaging observation error estimation methods are to usually estimate the error of each observation position by substituting the error parameters into the iterative reconstruction process, which has a huge calculation cost. In this paper, by analysing the relationship between imaging results of single-observation sampling data and error parameters, a SAR observation error estimation method based on maximum relative projection matching is proposed. First, the method estimates the precise position parameters of the reference position by the sparse reconstruction method of joint error parameters. Second, a relative error estimation model is constructed based on the maximum correlation of base-space projection. Finally, the accurate error parameters are estimated by the Broyden–Fletcher–Goldfarb–Shanno method. Simulation and measured data of microwave anechoic chambers show that, compared to the existing methods, the proposed method has higher estimation accuracy, lower noise sensitivity, and higher computational efficiency.

scholarly journals Histogram Adjustment of Images for Improving Photogrammetric Reconstruction

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4654
Author(s):  
Piotr Łabędź ◽  
Krzysztof Skabek ◽  
Paweł Ozimek ◽  
Mateusz Nytko
Keyword(s):  
Image Enhancement ◽  
High Efficiency ◽  
Color Image ◽  
Histogram Equalization ◽  
Reconstruction Accuracy ◽  
Reconstruction Process ◽  
Reference Models ◽  
Color Models ◽  
Selection Of

The accuracy of photogrammetric reconstruction depends largely on the acquisition conditions and on the quality of input photographs. This paper proposes methods of improving raster images that increase photogrammetric reconstruction accuracy. These methods are based on modifying color image histograms. Special emphasis was placed on the selection of channels of the RGB and CIE L*a*b* color models for further improvement of the reconstruction process. A methodology was proposed for assessing the quality of reconstruction based on premade reference models using positional statistics. The analysis of the influence of image enhancement on reconstruction was carried out for various types of objects. The proposed methods can significantly improve the quality of reconstruction. The superiority of methods based on the luminance channel of the L*a*b* model was demonstrated. Our studies indicated high efficiency of the histogram equalization method (HE), although these results were not highly distinctive for all performed tests.

Material Surface Reconstruction Based on Light Projection

2010 ◽  
Vol 143-144 ◽  
pp. 768-772
Author(s):  
Shao Yan Gai ◽  
Fei Peng Da
Keyword(s):  
Surface Reconstruction ◽  
Three Dimensional ◽  
Shape Reconstruction ◽  
Material Surface ◽  
Reconstruction Method ◽  
Object Surface ◽  
Reconstruction Process ◽  
Dimensional Shape ◽  
Three Dimensional Shape ◽  
Vision Geometry

A surface reconstruction method for material shape analysis is presented. The three-dimensional shape reconstruction system detects object surface based on optical principle. A series of gratings are projected to the object, and the projected gratings are deformed by the object surface. From images of the deformed gratings, three-dimensional profile of the material surface can be obtained. The basic aspects of the method are discussed, including the vision geometry, the light projection and code principle. The proposed method can deal with objects with various discontinuities on the material surface, thus increasing the flexibility and robustness of shape reconstruction process. The experimental results show the efficiency of the method, the material surface can be reconstructed with high precision in various applications.

Computer Hard Disk Planeness Vision Measurement System Calibration Based on Light Plane Constraint

2013 ◽  
Vol 475-476 ◽  
pp. 63-67
Author(s):  
Rui Yin Tang ◽  
Zhou Mo Zeng ◽  
Peng Fei Li
Keyword(s):  
Nonlinear Model ◽  
Constraint Equation ◽  
Hard Disk ◽  
Calibration Method ◽  
Calibration Target ◽  
System Calibration ◽  
Vision Measurement ◽  
Light Plane ◽  
Fitting Method ◽  
Extrinsic Parameters

This paper proposed a calibration method of sheet-of-light vision measurement sensor based on light plane constraint. Through capturing 12 images of different direction from homemade circular calibration target, the center of the circle and the light stripe is extracted based on Halcon platform of Germany. The experimental results obtained the intrinsic parameters, extrinsic parameters and radial distortion coefficient of the nonlinear model. At the same time the light plane constraint equation is got based on PCA plane fitting method. The results show that the calibration method is simple and reliable, and the method does not need any auxiliary adjustment. The work laid the better foundation for hard disk planeness vision measurement.

Accuracy-Complexity Trade-Off for the Signal Reconstruction of Multifunctional Sensors

2013 ◽  
Vol 706-708 ◽  
pp. 618-622
Author(s):  
Xian Guang Fan ◽  
Xin Wang ◽  
Jing Lin Wu ◽  
Yong Zuo
Keyword(s):  
Optimization Design ◽  
Signal Reconstruction ◽  
Spline Approximation ◽  
Significant Loss ◽  
Reconstruction Method ◽  
Reconstruction Accuracy ◽  
Trade Off ◽  
B Spline ◽  
On Chip ◽  
Chip Signal

The on-chip signal reconstruction method based on B-spline approximation and Extended Kalman Filter (EKF) for multifunctional sensors has been studied previously. In this paper, we focus on the design for reducing the complexity of the reconstruction method without significant loss of reconstruction accuracy. The two-objective optimization design framework is proposed, where the reconstruction accuracy and complexity are considering as two conflicting costs to be decreased jointly. Genetic Algorithm (GA) is presented to achieve the accuracy-complexity trade-off by optimizing the B-spline structure parameters, i.e. the dimensions of knot vectors. The experimental results show that the proposed method provides a good improvement to the B-spline and EKF based on-chip signal reconstruction method.

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