scholarly journals Subset-based stereo calibration method optimizing triangulation accuracy

2021 ◽  
Vol 7 ◽  
pp. e485
Author(s):  
Oleksandr Semeniuta
Keyword(s):  
Stereo Vision ◽  
Principal Component ◽  
Calibration Method ◽  
Image Pair ◽  
Calibration Pattern ◽  
Stereo Calibration ◽  
Image Pairs ◽  
Industrial Cameras ◽  
Random Nature ◽  
Calibration Parameters

Calibration of vision systems is essential for performing measurement in real world coordinates. For stereo vision, one performs stereo calibration, the results of which are used for 3D reconstruction of points imaged in the two cameras. A common and flexible technique for such calibration is based on collection and processing pairs of images of a planar chessboard calibration pattern. The inherent weakness of this approach lies in its reliance on the random nature of data collection, which might lead to better or worse calibration results, depending on the collected set of image pairs. In this paper, a subset-based approach to camera and stereo calibration, along with its implementation based on OpenCV, is presented. It utilizes a series of calibration runs based on randomly chosen subsets from the global set of image pairs, with subsequent evaluation of metrics based on triangulating the features in each image pair. The proposed method is evaluated on a collected set of chessboard image pairs obtained with two identical industrial cameras. To highlight the capabilities of the method to select the best-performing calibration parameters, a principal component analysis and clustering of the transformed data was performed, based on the set of metric measurements per each calibration run.

Binocular Stereo Vision Calibration System Implementation of Grid Strain Measurement in Sheet Forming

2013 ◽  
Vol 397-400 ◽  
pp. 1547-1551
Author(s):  
Hui Yu Xiang ◽  
Bao An Han ◽  
Zhe Li ◽  
Jia Jun Huang
Keyword(s):  
Stereo Vision ◽  
Strain Measurement ◽  
Calibration Method ◽  
Sheet Forming ◽  
Calibration System ◽  
Camera Model ◽  
Distortion Factor ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Stereo Calibration

For the research of camera calibration in the system of grid strain measurement in sheet forming, the pinhole camera model, the nonlinear model of the camera and the binocular stereo model are analyzed, drawing a binocular stereo calibration method based on HALCON, which detailedly describes the calibration principle and specific calibration process. A binocular stereo vision calibration system based on VC6.0 is established, by which the influence on camera focus, distortion factor and principle points from the number of calibration images is verified by experiments.

Jupiter's Zonal Vorticity Profile Observed by JunoCam

2021 ◽  
Author(s):  
Gerald Eichstädt ◽  
John Rogers ◽  
Glenn Orton ◽  
Candice Hansen
Keyword(s):  
Monte Carlo ◽  
Wind Profile ◽  
Image Pair ◽  
Stereo Correspondence ◽  
Cyclonic Vorticity ◽  
Latitude Range ◽  
Novel Structure ◽  
The Mean ◽  
Image Pairs ◽  
Cloud Tops

<p>We derive Jupiter's zonal vorticity profile from JunoCam images, with Juno's polar orbit allowing the observation of latitudes that are difficult to observe from Earth or from equatorial flybys.  We identify cyclonic local vorticity maxima near 77.9°, 65.6°, 59.3°, 50.9°, 42.4°, and 34.3°S planetocentric at a resolution of ~1°, based on analyzing selected JunoCam image pairs taken during the 16 Juno perijove flybys 15-30. We identify zonal anticyclonic local vorticity maxima near 80.7°, 73.8°, 62.1°, 56.4°, 46.9°, 38.0°, and 30.7°S.  These results agree with the known zonal wind profile below 64°S, and reveal novel structure further south, including a prominent cyclonic band centered near 66°S. The anticyclonic vorticity maximum near 73.8°S represents a broad and skewed fluctuating anticyclonic band between ~69.0° and ~76.5°S, and is hence poorly defined. This band may even split temporarily into two or three bands.  The cyclonic vorticity maximum near 77.9°S appears to be fairly stable during these flybys, probably representing irregular cyclonic structures in the region. The area between ~82° and 90°S is relatively small and close to the terminator, resulting in poor statistics, but generally shows a strongly cyclonic mean vorticity, representing the well-known circumpolar cyclone cluster.</p><p>The latitude range between ~30°S and ~85°S was particularly well observed, allowing observation periods lasting several hours. For each considered perijove we selected a pair of images separated by about 30 - 60 minutes. We derived high-passed and contrast-normalized south polar equidistant azimuthal maps of Jupiter's cloud tops. They were used to derive maps of local rotation at a resolution of ~1° latitude by stereo-corresponding Monte-Carlo-distributed and Gauss-weighted round tiles for each image pair considered. Only the rotation portion of the stereo correspondence between tiles was used to sample the vorticity maps. For each image pair, we rendered ~40 vorticity maps with different Monte-Carlo runs. The standard deviation of the resulting statistics provided a criterion to define a valid area of the mean vorticity map. Averaging vorticities along circles centered on the south pole returned a zonal vorticity profile for each of the perijoves considered. Averaging the resulting zonal vorticity profiles built the basis for a discussion of the mean profile.</p><p>JunoCam also images the northern hemisphere, at higher resolution but with coverage restricted to a briefer time span and smaller area due to the nature of Juno's elliptical orbit, which will restrict our ability to obtain zonal vorticity profiles.</p>

Research on Ranging Method Based on Binocular Stereo Vision

2014 ◽  
Vol 945-949 ◽  
pp. 2075-2081 ◽  
Author(s):  
Xue Zhi Lv ◽  
Mei Ting Wang ◽  
Yong Feng Qi ◽  
Xue Mei Zhao ◽  
Hao Dong
Keyword(s):  
Camera Calibration ◽  
Stereo Vision ◽  
Experimental Platform ◽  
Binocular Stereo Vision ◽  
Parallel Arrangement ◽  
Binocular Stereo ◽  
Contour Boundary ◽  
Measurement Object ◽  
Stereo Calibration ◽  
Left And Right

Binocular stereo vision ranging method taking contour boundary center of measurement object as matching features was investigated. And experimental platform for binocular stereo vision ranging system was built up. The stereo vision ranging system comprised four modules: camera calibration, stereo calibration, stereo rectification and features extraction. Firstly, the intrinsic parameters of single camera were obtained by camera calibration and relative pose of two cameras was obtained by stereo calibration. Then the left and right images were rectified into a frontal parallel arrangement by Bouguet’s method. The edge pixels of contours were detected by image processing. Then the disparity and the distance was calculated taking contour center as matching features. Finally, measurement error analysis was performed to verify the proposed method with good practicability.

Novel Calibration Method for Stereo Vision Sensor Using Flexible Target

2013 ◽  
Vol 33 (3) ◽  
pp. 0315001
Author(s):  
刘震 Liu Zhen ◽  
尚砚娜 Shang Yanna
Keyword(s):  
Stereo Vision ◽  
Calibration Method ◽  
Vision Sensor

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 Calibration of Industrial Cameras for Aerial Photogrammetric Mapping

2020 ◽  
Vol 12 (19) ◽  
pp. 3130
Author(s):  
Jakub Kolecki ◽  
Przemysław Kuras ◽  
Elżbieta Pastucha ◽  
Krystian Pyka ◽  
Maciej Sierka
Keyword(s):  
Survey Methodology ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Test Field ◽  
Baseline Method ◽  
Field Calibration ◽  
Custom Software ◽  
Single Process ◽  
Industrial Cameras ◽  
Very High

This paper details the development of a camera calibration method purpose-built for use in photogrammetric survey production. The calibration test field was established in a hangar, where marker coordinates were measured using a high-precision survey methodology guaranteeing very high accuracy. An analytical model for bundle adjustment was developed that does not directly use the coordinates of field calibration markers but integrates bundle adjustment and survey observations into a single process. This solution, as well as a classical calibration method, were implemented in a custom software, for which the C++ source code repository is provided. The method was tested using three industrial cameras. The comparison was drawn towards a baseline method, OpenCV implementation. The results point to the advantages of using the proposed approach utilizing extended bundle adjustment.

The Implementation of Distance Measurement Using Binocular Vision

2012 ◽  
Vol 490-495 ◽  
pp. 711-715
Author(s):  
Alin Hou ◽  
Ying Geng ◽  
Xue Cui ◽  
Wen Ju Yuan ◽  
Feng Guang Shi
Keyword(s):  
Camera Calibration ◽  
Binocular Vision ◽  
Stereo Vision ◽  
Distance Measurement ◽  
Simulation Experiments ◽  
Visual Measurement ◽  
Actual Distance ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Image Pairs

The method of distance measurement based on binocular stereo vision is presented in this paper. The model of camera imaging is established and the process of camera calibration is described. Interior and external parameters of two cameras are calculated by HALCON. The system of visual measurement is fabricated. The parallax measurement of the image pairs is accomplished. The simulation experiments of distance measurement have been done and the calculated results can be in accordance with the actual distance.

An Automatic Self-Calibration Approach for Wide Baseline Stereo Cameras Using Sea Surface Images

2015 ◽  
Vol 03 (04) ◽  
pp. 277-290 ◽  
Author(s):  
Han Wang ◽  
Wei Mou ◽  
Xiaozheng Mou ◽  
Shenghai Yuan ◽  
Soner Ulun ◽  
...  
Keyword(s):  
Feature Detection ◽  
Depth Estimation ◽  
Calibration Method ◽  
Sea Surface ◽  
Distant Object ◽  
Self Calibration ◽  
Calibration Pattern ◽  
Left And Right ◽  
Calibration Approach ◽  
Surface Images

Stereo rig with wide baseline is necessary when accurate depth estimation for distant object is desired. However, in order to make calibration pattern to be viewed from both left and right cameras, the wider the baseline the bigger the calibration pattern is required. In contrast to the traditional stereo calibration method using calibration pattern, we propose a self-calibration approach that can estimate cameras' rotation matrices for stereo rig with wide baseline (3 m). Given images taken from left and right cameras, the relative roll and pitch angles between two cameras are recovered by aligning sea horizon in left and right images. The pitch angle is estimated by making the projections of one point at infinite distance appear at the same location in both images. A photometric minimization is applied to refine the rotation parameters. Compared with conventional checkerboard-based calibration techniques which require extra equipments or personnel, our approach only needs a pair of sea images. Moreover, unlike most self-calibration approaches, feature detection and matching are not required which makes it possible to apply our approach on featureless images. As a result, it is flexible and easy to implement our approach on sea surface images. Real world experiments demonstrate the feasibility of our approach.

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