Stereo Calibration Method Research Articles

Neural-Network-Based Model-Free Calibration Method for Stereo Fisheye Camera.

The fisheye camera has a field of view (FOV) of over 180°, which has advantages in the fields of medicine and precision measurement. Ordinary pinhole models have difficulty in fitting the severe barrel distortion of the fisheye camera. Therefore, it is necessary to apply a nonlinear geometric model to model this distortion in measurement applications, while the process is computationally complex. To solve the problem, this paper proposes a model-free stereo calibration method for binocular fisheye camera based on neural-network. The neural-network can implicitly describe the nonlinear mapping relationship between image and spatial coordinates in the scene. We use a feature extraction method based on three-step phase-shift method. Compared with the conventional stereo calibration of fisheye cameras, our method does not require image correction and matching. The spatial coordinates of the points in the common field of view of binocular fisheye camera can all be calculated by the generalized fitting capability of the neural-network. Our method preserves the advantage of the broad field of view of the fisheye camera. The experimental results show that our method is more suitable for fisheye cameras with significant distortion.

A Stereo Calibration Method of Multi-Camera Based on Circular Calibration Board

In the application of 3D reconstruction of multi-cameras, it is necessary to calibrate the camera used separately, and at the same time carry out multi-stereo calibration, and the calibration accuracy directly affects the effect of the 3D reconstruction of the system. Many researchers focus on the optimization of the calibration algorithm and the improvement of calibration accuracy after obtaining the calibration plate pattern coordinates, ignoring the impact of calibration on the accuracy of the calibration board pattern coordinate extraction. Therefore, this paper proposes a multi-camera stereo calibration method based on circular calibration plate focusing on the extraction of pattern features during the calibration process. This method preforms the acquisition of the subpixel edge acquisition based on Franklin matrix and circular feature extraction of the circular calibration plate pattern collected by the camera, and then combines the Zhang’s calibration method to calibrate the camera. Experimental results show that compared with the traditional calibration method, the method has better calibration effect and calibration accuracy, and the average reprojection error of the multi-camera is reduced by more than 0.006 pixels.

3-D Reconstruction of Bubble Flow Field Based on the Method of Multivision by Rough-Precise Location Algebraic Reconstruction Technique

To acquire the distribution of gas–liquid two-phase flow accurately, 3-D reconstruction method of bubble flow field with multiview cameras was studied in this work. Three cameras were employed to take bubble images from different angles, and the three-camera stereo calibration method is proposed to obtain the mapping relationship between bubble flow field and projection image. Then, an improved technique named rough-precise location algebraic reconstruction technique (ART) based on multiview images was developed to reconstruct the bubble flow field. The calibration result is used for rough location of bubbles and the ART is employed for precise location. Based on the simulation experiment, the mean Intersection-over-Union of the proposed method is 93.84% and the mean reconstruction time is 0.081 s/voxel, which are faster and more accuracy than traditional ART. The reconstruction experiments of bubble flow field have illustrated that the proposed method is of less noise and more accurate than the parallax method. Meanwhile, the proposed method solves the bubble overlapping problem to some extent.

Subset-based stereo calibration method optimizing triangulation accuracy.

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.

Calibrating stereo-digital image correlation system using synthetic speckle-pattern calibration target

We describe an alternative stereo calibration method for stereo-digital image correlation (stereo-DIC) using computer-simulated speckle-pattern calibration targets and a DIC-based control points matching technique. The present work refines and extends the recently proposed camera calibration method to stereo calibration, which is an essential part of stereo-DIC measurement. In the proposed calibration method, the calibration target is generated by displaying a synthetic speckle pattern on a commercial tablet. On the simulated speckle pattern, a group of control points is specified with flexible location and number, which is further precisely matched to the captured calibration images using the well-developed subset-based DIC algorithm. These precisely matched control points are subsequently used to calibrate the intrinsic and extrinsic parameters of the stereo-DIC system with stereo calibration algorithm. For better accuracy, the error in the manufacture of the calibration target is also considered and compensated. As a flexible number of control point matches are registered with high accuracy and strong robustness, the presented stereo calibration method using synthetic speckle pattern calibration target offers higher calibration accuracy than that based on a calibration target with a limited number of designated features, such as checkerboard target and circular point target. After being demonstrated by a set of simulated calibration tests, the proposed stereo calibration method was applied to calibrate a real stereo-DIC system, which was then used to measure 3D full-field shapes and displacements. The results confirm the effectiveness and accuracy of the proposed stereo calibration method for stereo-DIC applications.

Stereo calibration of binocular ultra-wide angle long-wave infrared camera based on an equivalent small field of view camera

ABSTRACTIn this paper, a stereo calibration method for binocular ultra-wide angle long-wave infrared camera is proposed on the basis of an equivalent small field of view camera. Extrinsic parameters are calibrated through the corrected images from the left and right cameras. They can be viewed as images taken by a small field of view camera. The calibration procedure consists of three steps: monocular calibration, distortion correction and extrinsic parameters calibration. In order to evaluate the accuracy of the method, stereo vision of the camera is modelled and a 3D reconstruction approach is presented. A series of experiments, including intrinsic parameters, extrinsic parameters and 3D reconstruction, are conducted to validate the proposed method. The results show that the baseline length error decreases to 0.67%, and the relative error for the 3D reconstruction of corners is smaller than 8.11%. In contrast to the common stereo calibration method, it improves calibration accuracy.

Stereo calibration with absolute phase target.

Stereo cameras have been widely used for three-dimensional (3D) photogrammetry, and stereo calibration is a crucial process to estimate the intrinsic and extrinsic parameters. This paper proposes a stereo calibration method with absolute phase target by using horizontal and vertical phase-shifting fringes. The one-to-one mapping from the world points to the image points that can be recovered by referring to the absolute phase and then used to calibrate the stereo cameras. Compared with traditional methods that only use feature points within the overlapping field-of-view (FOV), the proposed method can use all feature points within the overlapping and non-overlapping FOVs. Besides, since phase is more robust against camera defocusing than intensity, the target images can be captured regardless of the depth-of-field (DOF). With the advantages of whole-field capability and defocusing tolerability, the target placement becomes very flexible. Both simulations and experiment results demonstrate the robustness and accuracy of the proposed method.

Automated Detection of Branch Shaking Locations for Robotic Cherry Harvesting Using Machine Vision

Automation in cherry harvesting is essential to reduce the demand for seasonal labor for cherry picking and reduce the cost of production. The mechanical shaking of tree branches is one of the widely studied and used techniques for harvesting small tree fruit crops like cherries. To automate the branch shaking operation, different methods of detecting branches and cherries in full foliage canopies of the cherry tree have been developed previously. The next step in this process is the localization of shaking positions in the detected tree branches for mechanical shaking. In this study, a method of locating shaking positions for automated cherry harvesting was developed based on branch and cherry pixel locations determined using RGB images and 3D camera images. First, branch and cherry regions were located in 2D RGB images. Depth information provided by a 3D camera was then mapped on to the RGB images using a standard stereo calibration method. The overall root mean square error in estimating the distance to desired shaking points was 0.064 m. Cherry trees trained in two different canopy architectures, Y-trellis and vertical trellis systems, were used in this study. Harvesting testing was carried out by shaking tree branches at the locations selected by the algorithm. For the Y-trellis system, the maximum fruit removal efficiency of 92.9% was achieved using up to five shaking events per branch. However, maximum fruit removal efficiency for the vertical trellis system was 86.6% with up to four shakings per branch. However, it was found that only three shakings per branch would achieve a fruit removal percentage of 92.3% and 86.4% in Y and vertical trellis systems respectively.

Calibration and rectification of vertically aligned binocular omnistereo vision systems

Omnidirectional stereo vision systems have been widely used as primary vision sensors in intelligent robot 3D measurement tasks, which require stereo calibration and rectification. Current stereo calibration and rectification methods suffer from complex calculations or a lack of accuracy. This paper establishes a simple and effective equivalency between an omnidirectional stereo vision system and a perspective vision system by studying stereo calibration and rectification methods. First, we improved the stereo calibration method. By applying the essential matrix, the complicated calibration process of the original method is simplified. By using a manual extraction method to extract corner points, noise error is eliminated and high precision is ensured. Second, we propose a new rectification method. By using the proposed simple rectification model and calibration data, the baseline length and an accurate column-aligned image pair are easily obtained, which reduces the computation time. The proposed stereo calibration and rectification method can simply and effectively obtain two key parameters of the triangulation formula for 3D measurement tasks: baseline length and parallax. Using real data captured by equipment, we performed experiments covering all the necessary stages to obtain a high-performance omnidirectional stereo vision system. Statistical analyses of the experimental results demonstrate the effectiveness of the proposed method.

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

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

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.