Flexible Calibration Method Research Articles

A Novel Dynamic Light-Section 3D Reconstruction Method for Wide-Range Sensing

Existing galvanometer-based laser-scanning systems are challenging to apply in multi-scale 3D reconstruction because of the difficulty in achieving a balance between a high reconstruction accuracy and a wide reconstruction range. This paper presents a novel method that synchronizes laser scanning by switching the field-of-view (FOV) of a camera using multi-galvanometers. Beyond the advanced hardware setup, we establish a comprehensive geometric model of the system by modeling dynamic camera, dynamic laser, and their combined interaction. Furthermore, since existing calibration methods mainly focus on either dynamic lasers or dynamic cameras and have certain limitations, we propose a novel high-precision and flexible calibration method by constructing an error model and minimizing the objective function. The performance of the proposed method was evaluated by scanning standard components. The results show that the proposed 3D reconstruction system achieves an accuracy of 0.3 mm when the measurement range is extended to 1100 mm × 1300 mm × 650 mm. This demonstrates that for meter-scale reconstruction ranges, a sub-millimeter measurement accuracy is achieved, indicating that the proposed method realizes multi-scale 3D reconstruction and simultaneously allows for high-precision and wide-range 3D reconstruction in industrial applications.

Flexible Calibration Method for a Quad-Directional Stereo Vision Sensor Based on Unconstraint 3-D Target

Flexible Calibration Method for a Quad-Directional Stereo Vision Sensor Based on Unconstraint 3-D Target

Flexible Calibration Method and Application of Passenger Car HUD Detection Based on Collaborative Robot

Flexible Calibration Method and Application of Passenger Car HUD Detection Based on Collaborative Robot

Equivalent distortion imaging model-based calibration method for a projection moiré system using combined lenses

The projection moiré method is a noncontact full-field optical topography measurement technique, which requires a precise model and corresponding calibration method; however, the existing models and calibration methods are either incompatible with system distortion or involve complex experimental operations. This study presents an equivalent distortion imaging model coupled with a flexible calibration method that overcomes such shortcomings. The proposed model is constructed by considering the stacking effect of the distortions of the two lenses and the misalignment between the optical axes. The corresponding calibration method leverages the existing camera calibration method to avoid complex operations. The proposed model has high precision owing to its ability to describe the complex imaging of the system. Moreover, the calibration is flexible and requires far fewer operations than with the two-stage calibration method. Both simulations and experiments verify the effectiveness of the proposed method.

A flexible calibration method with multi-stage optimization for the axial error of mobile mapping systems

Mobile mapping systems, which are equipped with a laser scanner, panoramic camera, and inertial navigation system, can flexibly and efficiently obtain precision point clouds. However, these systems require re-installation for each mission, which causes displacement errors in the instruments, resulting in discrepancies between multiple collections of data. The existing calibration methods usually require additional control targets settled in a managed field survey. Furthermore, the point clouds obtained with mobile mapping systems do not follow the common assumption of rigid transformation. To alleviate the above problems, we propose a flexible in-situ calibration method that only requires data collected in a round-trip survey pattern and conducts a self-calibration of the placement parameters with meticulously designed exact point matching. Specifically, because the accuracy of the existing feature-based registration method is not sufficient to acquire the exact correspondences of point clouds and to prune the outliers in correspondence searching. We propose novel pruning and refining approaches to obtain exact point-to-point correspondences between the round-trip point clouds. From systematic analyses of the coupling between different factors, we then construct a simplified error model that takes into account the a priori rotation- and translation-weighted observations. Finally, to alleviate the correlation effects between different parameters, we decouple the least-squares solver into several stages and obtain robust self-calibration parameters. Surveying experiments show that the flexible calibration method proposed in this paper is both effective and feasible in improving the accuracy of point clouds in overlapping areas, and can reduce the inconsistency of the calibrated point clouds by 37.02%.

Demonstration of a simple and flexible calibration method for structured light system

The calibration of the system’s geometric parameters is always an important step in 3D topography measurement based on fringe projection profilometry. However, the traditional calibration method needs to be realized by the implementation of an electric guide rail, which exhibits certain problems, such as complicated operation and inconvenient carrying. Along these lines, in this work, a new simple and flexible calibration method is introduced. For the proposed method, a round calibration board only needs to be moved arbitrarily many times within the depth of field of the camera and projector. By using the existing camera calibration method, each calibration plate position and pose can be derived, while the phase of every pixel and the height data, as well as the phase of every pixel-height mapping relationship, were established. In addition, the rational function fitting method was used to accurately estimate the phase distribution of the black area of the calibration plate, avoiding thus the influence of the phase artifacts caused by high-contrast calibration targets. The minimum root mean square error (RMSE) of the experimental results was 0.074 mm. Compared with the traditional method, our approach is more flexible and convenient, and has no loss of reliability.

Accurate and flexible calibration method for a 3D microscopic structured light system with telecentric imaging and Scheimpflug projection.

3D imaging and metrology of complex micro-structures is a critical task for precision manufacturing and inspection. In this paper, an accurate and flexible calibration method for 3D microscopic structured light system with telecentric imaging and Scheimpflug projector is proposed. Firstly, a fringe projection 3D microscopy (FP-3DM) system consisting of a telecentric camera and a Scheimpflug projector is developed, which can take full advantage of the depth of field (DOF) and increase the measurement depth range. Secondly, an accurate and flexible joint calibration method is proposed to calibrate the developed system, which utilizes the established pinhole imaging model and Scheimpflug distortion model to calibrate telecentric imaging, and fully considers the correction and error optimization of the Scheimpflug projection model. Meanwhile, the optimized local homography is calculated to obtain more accurate sub-pixel correspondence between the camera and the projector, and the perspective-n-point (PnP) method make the 3D coordinate estimation of the feature point more accurate. Finally, a prototype and a dedicated calibration program are developed to realize high-resolution and high-precision 3D imaging. The experimental results demonstrate that the re-projection error is less than 1µm, and the 3D repeated measurement error based on feature fitting is less than 4µm, within the calibrated volume of 10(H)mm × 50(W)mm × 40(D)mm.

A flexible calibration method based on small planar target for defocused cameras

Complex engineering scenes increase the difficulty of camera calibration. High precision and easy operation are the necessary conditions to ensure successful calibration. This paper proposes a flexible calibration method for defocused cameras. Firstly, the initial calibration is completed by traditional Zhang's method. Then, the linear camera calibration based on the image pair is carried out. The image pair is obtained when the lens focuses on the calibration and measuring positions in sequence on the premise of keeping the calibration target stationary. The distortion coefficient is solved independently, the image distance conversion model is established to decouple the intermediate parameters, and finally, the linear solution of the camera parameters is obtained. The proposed method can complete the entire calibration process for a large-range vision measurement system using a small planar target. The number of calibration images required is close to Zhang's method. There is no need to fix the calibration target under multiple attitudes separately, which has strong operability. Experimental results show that the method is effective. The maximum calibration error of intrinsic parameters is 1.29%, and the maximum mean reprojection error is only 0.127 pixels. In addition, this method has good anti-noise performance and has satisfactory calibration accuracy under the action of different influencing factors, which indicates its broad applicability. The method can be applied to calibrating defocused cameras in special scenes such as engineering sites.

An Accurate and Flexible Calibration Method for 3d Microscopic Structured Light System with Telecentric Imaging and Scheimpflug Projection

An Accurate and Flexible Calibration Method for 3d Microscopic Structured Light System with Telecentric Imaging and Scheimpflug Projection

Demonstration of a Simple and Flexible Calibration Method for Structured Light System

Demonstration of a Simple and Flexible Calibration Method for Structured Light System

Flexible field calibration of transmitter location and orientation in accurate large-scale positioning system

An accurate large-scale positioning system is a high-precision distributed large-scale dimensional metrology system that is widely used in smart manufacturing and assembly applications. The system comprises multiple transmitters with locations and orientations that are typically calibrated based on auxiliary measurement equipment. However, the calibration method is complicated and time consuming. We propose a rapid and flexible calibration method based on the highly precise three-dimensional coordinate control network established by a calibration bar with an accuracy of ± 0.005 mm, including both estimation and optimization algorithms. Exploratory experiments were performed to validate the feasibility of the proposed calibration method. The results demonstrate that the proposed calibration method enables the repeated measurement errors to be maintained at <0.05 mm in X and Y and <0.04 mm in Z. The standard deviation after calibration was 0.18 mm in comparison with the laser tracker.

Flexible Extrinsic Parameter Calibration for Multicameras With Nonoverlapping Field of View

In many measurement applications using multicameras, there is often a nonoverlapping field of view (nFOV) between multicameras. It benefits greatly from having all of the cameras unified in a single coordinate frame by means of common spatial constraints. However, it is very difficult to establish common spatial constraints for accurate and quick calibration of the extrinsic parameters between multicameras in the case of long working distance, asymmetric working angle, or limited working space. To overcome these issues, we propose a flexible calibration method using a camera rig, which can be easily modeled as a hand–eye calibration problem and solved by only several sets of calibration images. To further improve the calibration accuracy, the camera intrinsic parameters, lens distortion coefficients, and extrinsic parameters are optimized simultaneously, similar to binocular calibration. However, this causes calculation instability of multiparameters. We extend the epipolar constraint to two images with an nFOV and add it into the optimization objective function together with the reprojection error, which ensures the basic consistency of intrinsic parameters before and after optimization, and reduce the fluctuation caused by the number of images involved in calibration. Experiments and application have proved that the proposed new methods are feasible and effective.

Accurate and Flexible Calibration Method for a Class of Visual Sensor Networks

Accurate and flexible calibration is a prerequisite for visual sensor networks to retrieve metric information from image data. This paper presents the design and implementation of an accurate and flexible calibration method for a class of visual sensor networks intended for 3D measurement and tracking in large volumes. The proposed method employs a generic camera model that is applicable for wide-angle lens cameras as well as for conventional cameras. It does not require all the employed cameras to share a common field of view, and only pairwise overlap is needed. In the calibration process, the poses between stereo cameras are first initialized using essential matrix decomposition and then optimized by the Levenberg-Marquardt algorithm. A weighted vision graph is proposed to select optimal transformation paths among cameras by using Dijkstra's shortest path algorithms for multi-camera calibration. Then, the global coordinates are constructed using a four-marker calibration triangle. Finally, a Unity3D-based virtual platform, in which the total number and configurations of cameras, as well as the environment scene, can be arbitrarily edited, is designed to test the proposed calibration algorithms. Extensive experiments based on synthetic and real data are performed to demonstrate the effectiveness of the proposed multi-camera calibration method. Experimental results show that the multi-camera calibration method is accurate and easy-to-implement in the presence of noise.

Flexible calibration method for visual measurement using an improved target with vanishing constraints.

In this paper, an improved calibration method based on vanishing constraints is proposed for calculating the extrinsic parameters of cameras. First, we come up with a improved target based on the conventional target with two groups of orthogonal parallel lines. The novel target is composed of two groups of parallel lines with a certain angle range from 80° to 90°, which can reduce the difficulty of target production and the manufacturing cost. Furthermore, in the optimization process, we design a new function with a more robust penalty factor instead of using the experienced values to get the extrinsic parameters for the binocular vision sensors. Finally, on account of using the improved target and the novel optimiazation function, the proposed method is more flexible and robust compared with Zhang's method.

Knee arthroscopic navigation using virtual-vision rendering and self-positioning technology.

Knee arthroscopy suffers from a lack of depth information and easy occlusion of the visual field. To solve these limitations, we propose an arthroscopic navigation system based on self-positioning technology, with the guidance of virtual-vision views. This system can work without any external tracking devices or added markers, thus increasing the working range and improving the robustness of the rotating operation. The fly-through view and global positioning view for surgical guidance are rendered through virtual-vision rendering in real time. The fly-through view provides surgeons with navigating the arthroscope in the internal anatomical structures using a virtual camera perspective. The global positioning view shows the posture of the arthroscope relative to the preoperative model in a transparent manner. The posture of the arthroscope is estimated from the fusion of visual and inertial data based on the visual-inertial stereo slam. A flexible calibration method that transforms the posture of the arthroscope in the physical world into the virtual-vision rendering framework is proposed for the arthroscopic navigation system with self-positioning information. Quantitative experiments for evaluating self-positioning accuracy were performed. For translation, the acquired mean error was 0.41 ± 0.28mm; for rotation, it was 0.11° ± 0.07°. The tracking range of the proposed system was approximately 1.4 times that of the traditional external optical tracking system for the rotating operation. Simulated surgical operations were performed on the phantom. The fly-through and global positing views were paired with original arthroscopic images for intuitive surgical guidance. The proposed system provides surgeons with both fly-through and global positioning views without a dependence on the traditional external tracking systems for surgical guidance. The feasibility and robustness of the system are evaluated, and it shows promise for medical applications.

High-precision and flexible calibration method of non-overlapping array cameras

In this paper, a high-precision and flexible intrinsic and extrinsic parameters calibration method for non-overlapping array cameras is proposed. In the camera array system, each camera employs an individual planar calibration board to achieve intrinsic parameters calibration. Without assistance of any other coded or un-coded target, the extrinsic parameters of array cameras can be flexibly calibrated based on close-range photogrammetry. To overcome the disadvantages of low precision under a large field of view in close-range photogrammetry, a refinement coordinates mapping (RCM) method to achieve high-precision reconstruction of targets is developed. The principles of single-camera calibration, close-range photogrammetry, and the extrinsic calibration method are introduced, respectively. Experiments are performed to analyze the stability of single-camera calibration and the world coordinates reconstruction of targets. The results of the re-projection error in extrinsic parameters calibration show that the developed RCM method has high precision.

Flexible and Accurate Calibration Method for Non-Overlapping Vision Sensors Based on Distance and Reprojection Constraints.

This paper addresses the problem of flexible and accurate global calibration for multiple non-overlapping vision sensors in a confined workspace. Instead of using an auxiliary calibration pattern, the proposed method uses one laser tracker and only its accessory target sphere to obtain all the 3D calibration points and then accomplish the initial estimation of pose between the vision sensors. Then, the 3D calibration points and the extrinsic parameters between vision sensors are further optimized via the bundle adjustment algorithm based on the distance and reprojection constraints. Experiments were conducted to validate the performance and the experimental results demonstrate that the distance error can be decreased from 3.5 mm to 0.8 mm after introducing the distance and reprojection constraints.

Calibration of a six-axis parallel manipulator based on BP neural network

Purpose This paper aims to provide a simple and flexible calibration method of parallel manipulators for improving the position accuracy only using partial pose information. Design/methodology/approach The overall idea of this method is to use BP neural network to fit the relationship between calibration parameters and measurement parameters and then adjust calibration parameters according to measurements. Findings The calibration method significantly improves the position accuracy of the six-axis parallel manipulator. Simulation shows that the accuracy can be improved by increasing the number of positions consisted of samples to train BP neural network, and when the position number is increased, the descent velocity of fitting error is decreased. Originality/value The method is general for various parallel mechanisms and simple for measurement process. It can be applied to the calibration of various mechanisms without analyzing the mathematical relationship between measurements and calibration parameters. The measurement parameters can be flexibly selected to simplify measurement process, which saves calibration cost and time.

Flexible method for improved transmitter parameter calibration in accurate large-scale positioning system

An accurate large-scale positioning system is a three-dimensional workspace measuring and positioning the laser scanning-based system that is widely used in smart manufacturing and assembly applications. The system includes laser transmitters that are typically calibrated using one of two methods: a high-precision rotary table-dependent method or a three-dimensional (3-D) coordinate control network-dependent method. However, these methods are error-prone and inefficient. We propose a flexible calibration method that is based on the transmitter geometry and employs the characteristic angles of the transmitter as calibration targets that do not change with transmitter location or orientation. The proposed method also utilizes a calibration algorithm that is based on a highly precise 3-D coordinate control network and includes an optimization algorithm and an estimation algorithm to produce initial values. The results of Monte Carlo simulations indicate that the proposed method enables the characteristic angles to maintain accuracy within 3 arc sec. Furthermore, the results of verification experiments show that the proposed method decreases the deviation of each control point and the root-mean-square error to 0.075 and 0.052 mm, respectively.

Flexible calibration method of an FPP system based on a geometrical model and NLSM with fewer parameters: publisher's note.

This publisher's note amends the Funding section of Appl. Opt.58, A7 (2019)APOPAI0003-693510.1364/AO.58.0000A7.