Monocular Measurement Research Articles

基于旋转平台的全空间单目光笔测量方法

基于旋转平台的全空间单目光笔测量方法

An improved measurement method of size of mechanical parts based on monocular vision

During the monocular measurement of multiple mechanical parts with non-negligible thickness at the same time, the physical dimensions of the pixels on the upper and lower surface edges of the mechanical parts in the image taken by the camera are different, resulting in the deviation of the actual measurement results of the mechanical parts In this paper, a measurement method based on unit pixel size compensation is proposed. This method compensates the measurement data by the distance between the upper and lower surfaces of the mechanical parts and the camera, thus reducing or even eliminating the measurement error caused by the thickness of mechanical parts. The simulation results show that, under the same measuring platform, for the mechanical parts of different sizes and thicknesses, this method can achieve a significant improvement in measurement accuracy.

Validation of the driver ecological glare test

IntroductionThe present study proposes to validate the Driver Ecological Glare Test (DEGT), a test developed to measure the benefit of a headlight glare Advanced Driver Assistance System (ADAS), by comparing it to a laboratory glare test. Method: Twenty-four participants, aged from 55 to 70 years, were recruited to complete a visual examination, including monocular halo size measurement for both eyes using Vision Monitor device (MonCv3; Metrovision). An on-field evaluation took place at night at the UTAC CERAM test track to obtain disability glare measures using the DEGT. Results: A significant correlation was found between the two glare tests and Bland-Altman analysis reveals a good agreement with a bias of 73.7 arcmin between the halo size measurements obtained from the DEGT and Vision Monitor. The results of the present study demonstrate that the DEGT is a valid method to test halo size and is adapted to evaluate the benefits of an antiglare device for drivers in an ecological situation.

Adaptive forward vehicle collision warning based on driving behavior

Forward Vehicle Collision Warning (FCW) is one of the most important functions for the Advanced Driver Assistance System (ADAS). In this procedure, vehicle detection and distance measurement are core components, requiring accurate localization and estimation. In this paper, we propose a simple but efficient forward vehicle collision warning framework by aggregating monocular distance measurement and precise vehicle detection. In order to obtain forward vehicle distance, a quick camera calibration method which only needs three physical points to calibrate related camera parameters is utilized. As for the forward vehicle detection, a multi-scale detection algorithm that regards the result of calibration as distance prior is proposed to improve the precision. What’s more, traditional deterministic FCW approaches cannot be personalized for different drivers, which will lead to false warnings when drivers are in diverse driving status. Therefore, abnormal driver behaviors are introduced to make FCW adaptive. Specifically, the proposed adaptive FCW generates warnings by considering the different behaviors of the driver. Intensive experiments are conducted in our established real scene dataset and the results have demonstrated the effectiveness of the proposed framework.

Precise monocular vision-based pose measurement system for lunar surface sampling manipulator

Space manipulator has been playing an increasingly important role in space exploration due to its flexibility and versatility. This paper is to design a vision-based pose measurement system for a four-degree-of-freedom (4-DOF) lunar surface sampling manipulator relying on a monitoring camera and several fiducial markers. The system first employs double plateaus histogram equalization for the markers to improve the robustness to varying noise and illumination. The markers are then accurately extracted in sub-pixel based on template matching and curved surface fitting. Finally, given the camera parameters and 3D reference points, the pose of the manipulator end-effector is solved from the 3D-to-2D point correspondences by combining a plane-based pose estimation method with rigid-body transformation. Experiment results show that the system achieves high-precision positioning and orientation performance. The measurement error is within 3 mm in position, and 0.2° in orientation, meeting the requirements for space manipulator operations.

Passive measurement method of tree diameter at breast height using a smartphone

The accurate measurement of diameter at breast height (DBH) is essential to forest resources inventory, management, and carbon cycle modeling. Monocular vision passive measurement method based on a smartphone is a technique that allows for automatic, portable, and mobile measurement of DBH. Here, we propose a method for measuring the DBH of multiple trees from a single image taken by a smartphone camera, using machine vision and close-range photogrammetry technology. First, we present a visual segmentation approach based on an improved frequency-tuned saliency algorithm, which allows us to extract the trunk contour. Then, we establish a depth extraction model to calculate the depth of each tree. To calculate the DBH of the trees in the image, we establish an adaptive feature coordinate system for DBH measurement of multiple trees, which helps us to study the conversion relationship between the coordinate systems and establish the tree DBH measurement model. Furthermore, the tree DBH measurement model is established based on the rigid motion law between each space coordinate systems; we first establishes the mapping relationship between the pixel coordinate system and the object space coordinate system. Then, according to the depth information, we can obtain the coordinate of the DBH measurement position in the image plane coordinate system, and then derive the diameter at breast height from the image. Experiment results showed that the calculated DBH have a strong relationship with the truth values (RMSE = 0.217 cm). The method yields an average relative error of 2.32% at distances of 2–10 m. For trees with DBH values less than 20 cm, the absolute error is <0.237 cm; for larger trees, the relative error is less than 1.272%. These errors fall within the accuracy requirements of the continuous inventory of Chinese national forest resources.

Monocular Visual-IMU Odometry: A Comparative Evaluation of Detector–Descriptor-Based Methods

Monocular visual-inertial measurement unit (IMU) odometry has been widely used in various intelligent vehicles. As a popular technique, detector–descriptor-based visual-IMU odometry is effective and efficient due to the fact that local descriptors are robust against occlusions, background clutter, and abrupt content changes. However, to our knowledge, there is not a comprehensive and comparative evaluation study on the performance of different combinations of detectors and descriptors recently developed. In order to bridge this gap, we conduct such a comparative study in a unified framework. In particular, six typical routes with different lengths, shapes, and road scenes are selected from the well-known KITTI dataset. We first evaluate the performance of different combinations of salient point detectors and local descriptors using the six routes. Then, we tune the parameters of the best detector or descriptor obtained for each route, to further augment the results. This paper provides not only comprehensive benchmarks for assessing various algorithms but also instructive guidelines and insights for developing detectors and descriptors to handle different road scenes.

Target recognition of indoor trolley for humanoid robot based on piecewise fitting method

SummaryAlthough several studies have considered the problem of humanoid robots pushing carts, only a few have focused on the problem of robots moving heavy objects under monocular vision. This study proposes a target recognition and positioning method and a control method for a robot pushing a loaded trolley. A control system based on the humanoid robot NAO is developed and a monocular visual ranging method with segmented fitting is proposed to realize hardware control and target search and positioning for NAO. The ability of NAO to push a small cart with various weights using visual positioning is tested. The experimental results show that the average error of the monocular distance measurement method is 1.7 mm and that the target search and positioning is accurate. NAO can push a loaded cart that is 6.5 times its own weight.

基于点特征的单目视觉位姿测量算法

基于点特征的单目视觉位姿测量算法

基于EPNP算法的单目视觉测量系统研究

The method of pose measurement using computer vision is widely used in modern control, navigation, tracking and other fields. A monocular visual pose measurement method was studied and designd based on P4P rectangular distribution of planar target and EPNP algorithm in this paper. Firstly, a single camera was used to obtain the plane target image. After the image processing, the pixel coordinates of the four feature points were obtained, and the EPNP algorithm was used to perform the attitude calculation. Secondly, the simulation analysis of pose error measurement provides theoretical guidance and basis for improving attitude measurement accuracy. Finally, a coordinate system registration method combined with a high-precision two-dimensional turntable was proposed. The method was used to verify the accuracy of the three-direction attitude angles. The experimental results show that the rotation angle around the x and y axes is[-6, 6], the pose measurement error is less than 0.1 to meet the measurement application requirements.

Error analysis method for monocular vision pose measurement system

Error analysis method for monocular vision pose measurement system

Whole-field high precision point to point calibration method

The traditional camera calibration methods based on internal parameters and external parameters employ a uniform analytic function to meet the requirements of statistical optimization. It may fail in describing the whole measurement volume properly when the distortion is strong. A novel whole-field point to point calibration method is proposed, in which the mapping relationship between the pixel coordinates and world coordinates of each individual spatial point is described by look-up tables. To guarantee the high calculation accuracy of the world coordinates of each spatial point, a virtual telecentric optical projection technology is used to encode the phase of each spatial position by loading a carrier frequency to establish a virtual world coordinate system. Then the mapping tables between the eponymous pixel and the corresponding virtual world coordinates of each calibrated position with known height can be established employing polynomial fitting or interpolation methods. At last, the real world coordinates of each spatial point are calculated by removing the additional displacement caused by the carrier frequency. Employing our method, errors caused by system installation and lens distortion, etc. can be effectively ruled out. An exhaustive comparison between the proposed calibration method and the traditional 3D stereo target calibration (3DSTC) method based on pinhole model with optimization strategy is given. Our method yields more accurate calibration results than 3DSTC method because it is closer to the real physical model. Experiment results show the feasibility and validity of the proposed method. It is recommended to be used in monocular measurement system when higher accuracy is requested.

A monocular visual measurement system for UAV probe-and-drogue autonomous aerial refueling

PurposeThe purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling (AAR) for unmanned aerial vehicle, which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.Design/methodology/approachMethods and techniques for marker detection, feature matching and pose estimation have been designed and implemented in the visual measurement system.FindingsThe simple blob detection (SBD) method is adopted, which outperforms the Laplacian of Gaussian method. And a novel noise-elimination algorithm is proposed for excluding the noise points. Besides, a novel feature matching algorithm based on perspective transformation is proposed. Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.Practical implicationsThe visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.Originality/valueThe SBD method is used to detect the features and a novel noise-elimination algorithm is proposed. Besides, a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.

A Monocular Vision Measurement System of Three-Degree-of-Freedom Air-Bearing Test-Bed Based on FCCSP

A monocular vision-based pose measurement system is provided for real-time measurement of a three-degree-of-freedom (3-DOF) air-bearing test-bed. Firstly, a circular plane cooperative target is designed. An image of a target fixed on the test-bed is then acquired. Blob analysis-based image processing is used to detect the object circles on the target. A fast algorithm (FCCSP) based on pixel statistics is proposed to extract the centers of object circles. Finally, pose measurements can be obtained when combined with the centers and the coordinate transformation relation. Experiments show that the proposed method is fast, accurate, and robust enough to satisfy the requirement of the pose measurement.

Single-Camera-Based Method for Step Length Symmetry Measurement in Unconstrained Elderly Home Monitoring.

single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes. according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking. Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%. Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking. This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc. single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes. according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking. Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%. Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking. This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc.

Global homography calibration for monocular vision-based pose measurement of mobile robots

Compared with the size of a calibration board, the inspected area within the camera field of view is much bigger in many applications such as visual surveillance systems. In this paper, we present a global image-to-ground homography calibration method to obtain the mapping between the image and the planar scene lying in the whole camera field of view. The calibration approach is proposed by fusing multiple local homography matrices, with each of them only reflecting the relationship between a small calibration board and its corresponding small image part. By further calibrating a height-related homography, visual measurement can be extended for arbitrary planar surfaces with known heights. The proposed method presents such merits as no requirement for camera internal parameters, high calibration accuracy, and ease of implementation. Experimental results show that (1) the proposed global homography method achieves more accurate measurement results than the local homography method; (2) the height-related homography is calibrated with high accuracy; (3) the proposed approach can be used for mobile robot localization with accuracy close to the performance limit of a monocular camera.

The Relationship between Crystalline Lens Power and Refractive Error in Older Chinese Adults: The Shanghai Eye Study

PurposeTo report calculated crystalline lens power and describe the distribution of ocular biometry and its association with refractive error in older Chinese adults.MethodsRandom clustering sampling was used to identify adults aged 50 years and above in Xuhui and Baoshan districts of Shanghai. Refraction was determined by subjective refraction that achieved the best corrected vision based on monocular measurement. Ocular biometry was measured by IOL Master. The crystalline lens power of right eyes was calculated using modified Bennett-Rabbetts formula.ResultsWe analyzed 6099 normal phakic right eyes. The mean crystalline lens power was 20.34 ± 2.24D (range: 13.40–36.08). Lens power, spherical equivalent, and anterior chamber depth changed linearly with age; however, axial length, corneal power and AL/CR ratio did not vary with age. The overall prevalence of hyperopia, myopia, and high myopia was 48.48% (95% CI: 47.23%–49.74%), 22.82% (95% CI: 21.77%–23.88%), and 4.57% (95% CI: 4.05–5.10), respectively. The prevalence of hyperopia increased linearly with age while lens power decreased with age. In multivariate models, refractive error was strongly correlated with axial length, lens power, corneal power, and anterior chamber depth; refractive error was slightly correlated with best corrected visual acuity, age and sex.ConclusionLens power, hyperopia, and spherical equivalent changed linearly with age; Moreover, the continuous loss of lens power produced hyperopic shifts in refraction in subjects aged more than 50 years.

二维合作目标的单相机空间位姿测量方法

二维合作目标的单相机空间位姿测量方法

基于平行面多靶标标定的单目大视场平面测量

基于平行面多靶标标定的单目大视场平面测量

Computationally efficient visual–inertial sensor fusion for Global Positioning System–denied navigation on a small quadrotor

Because of the complementary nature of visual and inertial sensors, the combination of both is able to provide fast and accurate 6 degree-of-freedom state estimation, which is the fundamental requirement for robotic (especially, unmanned aerial vehicle) navigation tasks in Global Positioning System–denied environments. This article presents a computationally efficient visual–inertial fusion algorithm, by separating orientation fusion from the position fusion process. The algorithm is designed to perform 6 degree-of-freedom state estimation, based on a gyroscope, an accelerometer and a monocular visual-based simultaneous localisation and mapping algorithm measurement. It also recovers the visual scale for the monocular visual-based simultaneous localisation and mapping. In particular, the fusion algorithm treats the orientation fusion and position fusion as two separate processes, where the orientation fusion is based on a very efficient gradient descent algorithm, whereas the position fusion is based on a 13-state linear Kalman filter. The elimination of the magnetometer sensor avoids the problem of magnetic distortion, which makes it a power-on-and-go system once the accelerometer is factory calibrated. The resulting algorithm shows a significant computational reduction over the conventional extended Kalman filter, with competitive accuracy. Moreover, the separation between orientation and position fusion processes enables the algorithm to be easily implemented onto two individual hardware elements and thus allows the two fusion processes to be executed concurrently.