Calibration Frame Research Articles

Evaluating Linear Coral Growth Estimation Using Photogrammetry and Alternative Point Cloud Comparison Methods

Abstract. Corals are critical reef-building organisms, providing essential habitat and ecosystem services. Tracking coral growth over time indicates coral reef health, which can be measured using various established techniques. Several coral growth-related studies have successfully applied photogrammetry to a particular coral of various types. While the focus of previous work was on standardised data processing and, to a certain degree, on the assessment of different point cloud comparison methods (Lange et al. 2022), little attention has been given to the impact of camera calibration. This study measured the annual linear extension of five Acropora spp. colonies using photogrammetry and evaluated all stages of imagery processing. A high focus was given to the analysis of the camera calibration method and the validation of camera parameters derived using an in-situ calibration of coral images with scale bars placed in the camera's field of view. We demonstrate that this method is as reliable as the calibration using a calibration frame. This study also examined the impact of the different point cloud comparison methods for Acropora spp. More specifically, the derived point clouds are compared by applying the point-to-point and point-to-model methods and manually selecting 12 coral branch tips. Histograms derived from the comparison methods were analysed and deemed a suitable and efficient alternative approach for measuring the maximum growth rate of mature colonies over shorter time periods (1 year or less).

Experimental demonstration of improved reference-frame-independent quantum key distribution over 175km.

Reference-frame-independent (RFI) quantum key distribution (QKD) presents promising advantages, especially for mobile-platform-based implementations, as it eliminates the need for active reference frame calibration. While RFI-QKD has been explored in various studies, limitations in key rate and distance persist due to finite data collection. In this study, we experimentally demonstrate an improved RFI-QKD protocol proposed by Zhu et al. [Opt. Lett.47, 4219 (2022)10.1364/OL.470558], featuring a statistical quantity for bounding information leaked to Eve that exhibits more insensitivity to statistical fluctuations and more robustness to variations in the reference frame. Taking into account finite-size considerations and potential general attacks, RFI-QKD is implemented over a distance of 175 km in this work. We believe that our study extends the communication distance achievable by RFI-QKD, thereby constituting a notable advancement for its practical application.

Robotic photogrammetric underwater inspection of hydropower plants

Hydropower is the most important domestic source of renewable energy in Switzerland, accounting for around 57 % of domestic electricity production. The high intensity usage of hydropower plants results in high costs for regular maintenance and inspection, which are currently carried out through manual inspections by professional divers. The aim of this work is to develop a workflow for underwater photogrammetry with Remotely Operated Vehicles (ROV) to supplement or replace these dangerous and expensive dives. A calibration frame was developed to provide a scale reference for the data collected during the inspection. With different acquisition missions, investigations on camera calibration and 3D reconstruction were performed. The reconstruction of underwater objects was successfully implemented. Well- distributed control points provide accurate results as a point cloud with a sub-centimetre accuracy at object distances of up to 6 m. 80 % of the point cloud differ less than 1 cm from the reference scan.

36‐3: Research on Partitioned Color Calibration Principle and Frame Rate Reduction Technology Based on Liquid Crystal Displays

36‐3: Research on Partitioned Color Calibration Principle and Frame Rate Reduction Technology Based on Liquid Crystal Displays

Effective augmentation of front opening unified pod filter images

The front opening unified pods (FOUPs) are popular carriers in semi-conductor industry, and their automatic optical inspection relies on the sufficiency of images. Filter papers at the bottom of FOUP require frequent inspection, while obtaining their images is time-consuming. This work thus investigates augmenting images of filter papers using conventional interpolation and a recent generative adversarial network with variations, including numbers of epochs, usage of progressive learning, loss functions, and cross frame calibration. Drawbacks of interpolated images are exhibited. Results of sixteen models are quantitatively evaluated using the Fréchet inception distance (FID). The best FID among all models is fid = 0.102, and the distribution of generated images is close to that of real images. A user study is also conducted to investigate the authenticity of generated images. Our experiments reveal that given a limited number of training images, after proper geometric calibration, images synthesized by a generative adversarial network are qualified for data augmentation and substantially benefit industrial image classification tasks.

INTRODUCTION AND VALIDATION OF A NOVEL CALIBRATION FRAME

Abstract. The use of Photogrammetry is increasingly used by several disciplines, including marine science. Among others, the accuracy of a 3D model generated from images, depends on the quality of the calibration and stability of the camera used to capture the images. For the calibration an optimum 3D geometry is essential to minimise correlations between the camera’s interior orientation parameters. For the calibration, usually various different types of calibration frames are used. However, in practice, it can be challenging to use these frames when working in underwater environments. Calibration frames can be bulky, which makes them difficult to handle and transport, especially in boats where space is at a premium. This study aimed to develop a collapsible (and thereby portable) calibration frame, which is more practical for marine field data capture. The proposed collapsible calibration frame is validated in-air and underwater. Overall, three tests are performed. Firstly, the reliability of the frame is validated, i.e. if the collapsible frame can be put together in such a way that the Ground Control Points (GCPs) on the frame have unchanged positions relative to each other. The test showed a very small bias which could be removed by changing to a baseline assessment. Secondly, repeatability is validated, i.e. if the same results can be achieved for different software and camera combinations when using the same baselines. The test showed a clear downwards trend of the results for lower-grad cameras. However, all adjustments using the different software solutions and cameras show that the frame is suitable for application in-air. The final test is an underwater performance test which verified that the frame is usable achieving root-mean-squared error values of below 2 mm when using baselines.

Tool Frame Calibration for Robot-Assisted Ultrasonic Testing.

Tool frame calibration has been widely used in robot-assisted printing, welding, and grinding, but it is not suitable for ultrasonic testing because the robot is submerged in water. The purpose of this paper is to present a tool frame calibration method, which is suitable for improving the precision of ultrasonic testing. In uniform mediums, sound travels along a straight line like ray. A reflector is fixed in water to reflect ultrasound, which makes it possible to measure distances between incidence points on a reflector and tool center point (TCP) on an ultrasound transducer. In addition, the positions and poses of the end flange are recorded through a robot controller. Finally, an optimization method is applied to calculate the position and pose errors of the tool frame relative to the end flange according to such records. The presented method was implemented in an ultrasonic testing system. We selected 100 incidence points on the reflector to calculate the assembly errors of the transducer. The pulse amplitude rose obviously after calibration, which verifies that this is an effective method. Considering that ultrasonic transducers can be used as a measuring tool, this paper proposes a tool frame calibration method for ultrasonic testing robots without introducing other measuring devices, which draws the conclusion that tool frame can be calibrated through ultrasound.

A Novel Model Calibration Method for Active Magnetic Bearing Based on Deep Reinforcement Learning

Active magnetically suspended control moment gyro is a novel attitude control actuator for satellites. It is mainly composed of rotor, active magnetic bearing (AMB) and motor. As a crucial supporting component of control moment gyro, the performance of AMB is directly related to the stability of the rotor system and pointing precision of the satellites. Therefore, calibrating the parameters of AMB is essential for the realization of super-quiet satellites. This paper proposed a model calibration method, known as the deep reinforcement learning-based model calibration frame (DRLMC). First, the dynamics of magnetic bearing with damage degradation over its life cycle are modeled. Subsequently, the calibration process is formulated as a Markov Decision Process (MDP), and reinforcement learning (RL) is employed to infer the degradation parameters. In addition, experience replay and target network update mechanism are introduced to guarantee stability. Simulation results demonstrate that the proposed method identifies force-current factor of AMB during its degradation process effectively. Furthermore, additional experiments confirm the robustness of the DRLMC approach.

DIFFERENCES IN KINEMATIC PARAMETERS BETWEEN FIRST AND SECOND SERVES IN TENNIS BY ELITE PLAYERS OF THE GERMAN LEAGUE

The primary goal of this research was to determine the differences in kinematic parameters between the first and second serves in tennis among the elite players of the German league. The sample of respondents in this research consisted of 30 elite male senior players of the German League who have "Leistungklasse" from 1 to 7. The kinematic parameters that were analyzed are: Height of ball impact (KPVUL), Racket speed (KPBRE), Ball speed (KPBLO), The angle at the elbow joint of the arm that hits the ball (KPULZ), Oscillation of the vertical projection of the center of gravity of the body (KPOVP), Jump height (KPVSK), Ball launch height (KPVIL), The point of contact between the ball and the racket "sweetspot" (KPMLR), Ball rotation "Top spin" (KPRLO). The video recording required for kinematic analysis was acquired with two Casio EX-F1 digital cameras at a frequency of 200 images per second. The camera was placed at an angle of 900 in relation to the recording plane, and they were at a distance of 10 m. Space calibration was performed with the help of a calibration frame (200 x 200 cm). We have installed Zepp Tennis Smart Sensor 2.0 in the handle of the Wilson Pro Staff RF97 Autograph racket, using the Zepp Tennis application software. "Kinovea" software was used for service analysis and obtaining kinematic parameters from video recordings. By analyzing the results of the T-test for independent samples, it can be seen that there are statistically significant differences in five of the nine analyzed kinematic parameters : KPBRE – kinematic parameter of racket speed (Sig.=.000), KPBLO – kinematic parameter of ball speed (Sig.=.000), KPULZ – kinematic parameter angle in the elbow joint (Sig.=.000), KPMLR – kinematic parameter point of contact between the ball and the racket (Sig.=.000), as well as a variable KPRLO – kinematic parameter of ball rotation (Sig.=.000). Larger numeric values in variables: KPVUL – kinematic parameter ball impact height, KPOVP – kinematic parameter of oscillation of the vertical projection of the center of gravity of the body, KPVSK – kinematic parameter jump height and KPVIL – kinematic parameter ball impact height, show a difference but it is not enough to be statistically different. Key words: tennis, kinematic analysis, racket speed, Zepp sensor

Ultrasound Probe and Hand-Eye Calibrations for Robot-Assisted Needle Biopsy

In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ultrasound probe and to perform hand-eye calibration of the robot in order to establish a link between intra-operatively acquired ultrasound images and robot-assisted needle insertion. Based on a high-precision optical tracking system, novel methods for ultrasound probe and robot hand-eye calibration are proposed. Specifically, we first fix optically trackable markers to the ultrasound probe and to the robot, respectively. We then design a five-wire phantom to calibrate the ultrasound probe. Finally, an effective method taking advantage of steady movement of the robot but without an additional calibration frame or the need to solve the AX=XB equation is proposed for hand-eye calibration. After calibrations, our system allows for in situ definition of target lesions and aiming trajectories from intra-operatively acquired ultrasound images in order to align the robot for precise needle biopsy. Comprehensive experiments were conducted to evaluate accuracy of different components of our system as well as the overall system accuracy. Experiment results demonstrated the efficacy of the proposed methods.

Joint K-space and Image-space Parallel Imaging (KIPI) for accelerated chemical exchange saturation transfer acquisition.

To develop an auto-calibrated technique by joint K-space and Image-space Parallel Imaging (KIPI) for accelerated CEST acquisition. The KIPI method selects a calibration frame with a low acceleration factor (AF) and auto-calibration signals (ACS) acquired, from which the coil sensitivity profiles and artifact correction maps are calculated after restoring the k-space by GRAPPA. Then the other frames with high AF and without ACS can be reconstructed by SENSE and artifact suppression. The signal leakage due to the T2 -decay filtering in k-space compromises the SENSE reconstruction, which can be corrected by the artifact suppression algorithm of KIPI. The 2D and 3D imaging experiments were done on the phantom, healthy volunteer, and brain tumor patient with a 3T scanner. The proposed KIPI method was evaluated by retrospectively undersampled data with variable AFs and compared against existing parallel imaging methods (SENSE/auto, GRAPPA, and ESPIRiT). KIPI enabled CEST frames with random AFs to achieve similar image quality, eliminated the strong aliasing artifacts, and generated significantly smaller errors than the other methods (p < 0.01). The KIPI method permitted an AF up to 12-fold in both phase-encoding and slice-encoding directions for 3D CEST source images, achieving an overall 8.2-fold speedup in scan time. KIPI is a novel auto-calibrated parallel imaging method that enables variable AFs for different CEST frames, achieves a significant reduction in scan time, and does not compromise the accuracy of CEST maps.

Augmented Reality Based Video Shooting Guidance for Novice Users

Using mobile phones to shoot video is considerably common in our daily life. However, novice users have difficulty in controlling the camera properly due to lack of professional knowledge and skill. In this paper, in order to assist novice users in learning and imitating professional camera movement from watching high quality sample videos, we propose ARCAM, an Augmented Reality (AR) based video shooting guidance method for novice users. Using AR, we visualized the concept of camera movement and embedded it into natural scene to provide real-time guidance. User can follow the guidance while shooting video by matching a calibration frame to the guidance, to achieve the desired camera movement. We conducted a user study comparing the effectiveness of ARCAM to a traditional static arrow guidance. Results showed that ARCAM was more effective in helping users understand the camera work in the sample videos and move the camera with more accuracy. Our work provides insights on designing mobile video shooting application and suggests that AR has great potential in assisting novice video shooters.

Framework Design of Sports Image Analysis System Based on Player Behavior Information

Obtaining the data and information urgently needed by coaches and athletes through the processing of visual continuous images of sports is the most effective means and method in the current sport’s technical analysis. The sports image photography framework is an important tool for transforming the two-dimensional coordinates of sports technology images into three-dimensional space coordinates. The article proposes a calibration algorithm suitable for the two-plane calibration frame. The calculation is simpler than the DLT algorithm, and it is easy to program. The experimental results show that the system has good tracking effect of moving image key frames, high comprehensiveness, low redundancy and high recall rate.

A New Method for Quantifying 3D Skeletal Morphology in Living Subjects Using Low‐Dose Stereo Radiographs

Accurate and repeatable assessments of three‐dimensional (3D) skeletal morphology are critical to interpretations of vertebrate functional anatomy. In skeletal specimens, these goals can be accomplished using in‐silico models derived from 3D laser scan, photogrammetry, or computed tomography (CT) data. Assessments of skeletal morphology in living subjects, especially humans, are more challenging and are often either cost‐prohibitive (e.g., magnetic resonance) or expose subjects to high doses of ionizing radiation (e.g., CT). Here, we present a new, open‐source method for assessing 3D skeletal morphology using ultra‐low dose biplanar radiographs. Biplanar radiographs were obtained using an EOS Imaging System (EOS Imaging, Inc., Paris, France). A custom‐built calibration frame with radiopaque markers was scanned using this system on multiple days in multiple positions inside the scanning space. We quantified the 3D coordinates of markers by placing landmarks at the center of each marker in both anterior‐posterior and lateral radiographs. Landmark data for each scan were collected independently by two observers to determine inter‐observer error. 3D coordinates of landmarks in each scan differed by &lt;1 mm between observers, suggesting strong repeatability in assessing morphology of living subjects. To assess distortion in EOS images, we constructed a second calibration device, a flat plate with radiopaque markers at the corners of three squares with 10 cm, 20 cm, and 30 cm sides, respectively, surrounding an origin point. The calibration plate was scanned with the origin point at the center of the scan area and the sides of the squares parallel to the detectors. We identified distortion at the edges of EOS images which could significantly impact measurements on skeletal features near the margins of the scan area (i.e., hips, pelvis, lower limbs) and developed a method to mathematically correct for resulting distortion in landmark data. Finally, we demonstrate this method using measurements of iliac blade and spinous process orientation in a sample of living human participants. This method will be applicable to studies of multiple human cohorts, including symptomatic and asymptomatic groups, as well as to other biplanar radiograph platforms and study organisms.

A calibration-based method for interval reliability analysis of the multi-manipulator system

The multiple manipulators can construct a special multi-agent system with the distinction that the type can be serial or parallel according to their cooperative way. We proposed a comprehensive method to handle the problem of reliability estimation. The wide and narrow bound method are applied to calculate the interval reliability respectively when multiple manipulators work as the series system. Aims to decrease the system complexity and enhance the dynamic adjustment capability, the base frame calibration technique is presented to convert the series system to a parallel one, naturally the reliability can be improved significantly. A system composed by three manipulators is utilized as an example to illustrate the feasibility of the proposed method.

Machine Learning-Assisted Measurement Device-Independent Quantum Key Distribution on Reference Frame Calibration.

In most of the realistic measurement device-independent quantum key distribution (MDI-QKD) systems, efficient, real-time feedback controls are required to maintain system stability when facing disturbance from either external environment or imperfect internal components. Traditionally, people either use a “scanning-and-transmitting” program or insert an extra device to make a phase reference frame calibration for a stable high-visibility interference, resulting in higher system complexity and lower transmission efficiency. In this work, we build a machine learning-assisted MDI-QKD system, where a machine learning model—the long short-term memory (LSTM) network—is for the first time to apply onto the MDI-QKD system for reference frame calibrations. In this machine learning-assisted MDI-QKD system, one can predict out the phase drift between the two users in advance, and actively perform real-time phase compensations, dramatically increasing the key transmission efficiency. Furthermore, we carry out corresponding experimental demonstration over 100 km and 250 km commercial standard single-mode fibers, verifying the effectiveness of the approach.

APPLICATION OF 3D ANALYSIS TECHNOLOGY OF VISION SYSTEM IMAGE IN SPORTS MEDICINE

ABSTRACT Background: Objective: The study of sports biomechanics in sports medicine usually requires a special image analysis system (software) to obtain 3D kinematics data. Taking the swimming project in sports medicine as an example, 3D water images in water have always been relatively complicated and difficult. As light travels in different media, it will refract and reflect. When testing underwater movements, if only a land camera or an underwater camera is used for testing, the error caused by light refraction will be larger, which will affect the accuracy of the test data even more. Methods: Taking breaststroke movement as an example, a three-dimensional measurement method based on the Kwon3D movement analysis system is introduced. This method is different from the simple underwater camera test. It is a three-dimensional test method combining a land camera and an underwater camera. Two underwater cameras and two land cameras were used to simultaneously calibrate the water and underwater space with the same calibration frame in the experiment after analyzing and verifying the accuracy of 3D reconstruction. Results: The comprehensive reconstruction error is small, and the average relative error is less than 1%. Conclusions: The application of three-dimensional image analysis technology of vision systems in sports medicine is reasonable and worth promoting. Level of evidence II; Therapeutic studies - investigation of treatment results.

Cobot User Frame Calibration: Evaluation and Comparison between Positioning Repeatability Performances Achieved by Traditional and Vision-Based Methods

Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame calibration method that allows even non-expert users to perform the procedure effectively, reducing the possible mistakes that may arise in such contexts. The aim of this work was to quantitatively assess the performance of different user frame calibration procedures in terms of accuracy, complexity, and calibration time, to allow a reliable choice of which calibration method to adopt and the number of calibration points to use, given the requirements of the specific application. This has been done by first analyzing the performances of a Rethink Robotics Sawyer robot built-in user frame calibration method (Robot Positioning System, RPS) based on the analysis of a fiducial marker distortion obtained from the image acquired by the wrist camera. This resulted in a quantitative analysis of the limitations of this approach that only computes local calibration planes, highlighting the reduction of performances observed. Hence, the analysis focused on the comparison between two traditional calibration methods involving rigid markers to determine the best number of calibration points to adopt to achieve good repeatability performances. The analysis shows that, among the three methods, the RPS one resulted in very poor repeatability performances (1.42 mm), while the three and five points calibration methods achieve lower values (0.33 mm and 0.12 mm, respectively) which are closer to the reference repeatability (0.08 mm). Moreover, comparing the overall calibration times achieved by the three methods, it is shown that, incrementing the number of calibration points to more than five, it is not suggested since it could lead to a plateau in the performances, while increasing the overall calibration time.

Research on Improving Accuracy of MWD Based on Support Vector Classifier and K-Proximity Method

With the development of horizontal Wells and extended reach Wells in the field of oil and gas exploitation, it is of great significance to the development of MWD which can measure the drilling trajectory in real time. Therefore, in recent years, Measurement while drilling (MWD) has been widely recognized and rapidly developed in the field of precise target drilling. Accelerometers and fluxgates are related to well trajectory measurement in the MWD. The external environment and the processing and installation error of the sensor lead to some errors in the measured value. Deviation caused by environmental interference and installation error leads to the low control precision of drilling tool attitude. In view of the shortcomings of the current calibration methods and the time-consuming and complicated operation of the traditional tri-axis orthogonal inclinometer calibration, this paper proposes the attitude error calibration method of the MWD based on the support vector classifier and the K-proximity method. First, a neural network model is established based on the measured calibration results and the measurements errors. Then, the K-proximity method is used to further classify the drill tool attitude data, and a neural network model combining the K-proximity method is constructed. Secondly, the software and hardware experimental platform for on-line calibration of the slant meter while drilling is built by using the calibration frame and the geomagnetic sensor. Finally, the experimental results showed that the mean deviation of well inclination angle and tool face angle is controlled within ±0.2°, and the mean deviation of azimuth is controlled within ±0.5°, which verified that the algorithm can increase accurate of drilling tool attitude.

A New Frame-Based Calibration Method for Extended Octagonal Ring Transducers

HighlightsA simple frame was built to hold and apply uniaxial and biaxial loads to octagonal ring transducers for calibration.Similar results were obtained with the frame as with a universal tensile testing machine.The transducer outputs exhibited low cross-sensitivities and hysteresis (=0.4%), and R2 = 0.9998.The frame is portable and safe, and its concept can be adapted to take a wide range of non-gravitational loads.Abstract. An extended octagonal ring transducer (EORT) is a simple, single, and compact biaxial force measuring transducer, which is ideal for soil force measurement in tillage tool research. Calibration of EORTs is needed to ascertain their sensitivities and to determine an accurate calibration equation to convert voltage output to force measurement. Typically, calibration of EORTs involves the use of universal tensile testing machines, hydraulic systems and large gravitational loads (hanging weights) to apply loads. In this study, a simple calibration frame that enables application of non-gravitational loads was evaluated and used to hold and calibrate an EORT through both uniaxial and biaxial loading. The frame was suitable for both uniaxial and biaxial application of offset coincident force up to 3000 N and centered perpendicular force up to 1500 N. The EORT exhibited a strong linear relationship (R2 = 0.9998) between applied forces and voltage outputs, low hysteresis errors (=0.4%), and low cross-sensitivities (3.61% and 1.6% for coincident and perpendicular forces, respectively). Calibration equations developed from the primary bridge output data or from the biaxial loading data using the frame produced good force predictions, which also improved when taking into account the impacts of cross-sensitivity. The results confirmed that this calibration approach can integrate the interactions of output cross-sensitivity to deliver more accurate force prediction. Coefficients of determination of the relationships between applied and predicted forces were 0.9993 to 0.9996 and 0.9877 to 0.9984 for coincident and perpendicular forces, respectively. This calibration frame presents potential for safely applying large, non-gravitational loads in a contained and portable manner and its concept can easily be adapted to suit the scale of the transducer. Keywords: Biaxial loading, Cross-sensitivity, EORT calibration, Offset coincident force, Uniaxial loading.