Frequency and associated factors of accommodation and non-strabismic binocular vision dysfunction among medical university students

AIM:To investigate the frequency and associated factors of accommodation and non-strabismic binocular vision dysfunction among medical university students.METHODS:Totally 158 student volunteers underwent routine vision examination in the optometry clinic of Guangxi Medical University.Their data were used to identify the different types of accommodation and nonstrabismic binocular vision dysfunction and to determine their frequency.Correlation analysis and logistic regression were used to examine the factors associated with these abnormalities.RESULTS:The results showed that 36.71%of the subjects had accommodation and non-strabismic binocular vision issues,with 8.86%being attributed to accommodation dysfunction and 27.85%to binocular abnormalities.Convergence insufficiency(CI)was the most common abnormality,accounting for 13.29%.Those with these abnormalities experienced higher levels of eyestrain(χ2=69.518,P<0.001).The linear correlations were observed between the difference of binocular spherical equivalent(SE)and the index of horizontal esotropia at a distance(r=0.231,P=0.004)and the asthenopia survey scale(ASS)score(r=0.346,P<0.001).Furthermore,the right eye's SE was inversely correlated with the convergence of positive and negative fusion images at close range(r=-0.321,P<0.001),the convergence of negative fusion images at close range(r=-0.294,P<0.001),the vergence facility(VF;r=-0.234,P=0.003),and the set of negative fusion images at far range(r=-0.237,P=0.003).Logistic regression analysis indicated that gender,age,and the difference in right and binocular SE did not influence the emergence of these abnormalities.CONCLUSION:Binocular vision abnormalities are more prevalent than accommodation dysfunction,with CI being the most frequent type.Greater binocular refractive disparity leads to more severe eyestrain symptoms.

Binocular vision and abnormal head posture in children when watching television

AIM： To determine the association between the binocular vision and an abnormal head posture（AHP）when watching television（TV） in children 7-14 y of age.·METHODS： Fifty normal children in the normal group and 52 children with an AHP when watching TV in the AHP group were tested for spherical equivalents, far and near fusional convergence（FC） and fusional divergence（FD） amplitudes, near point of convergence, far and near heterophoria, accommodative convergence/accommodation ratio and stereoacuity. The values of these tests were compared between the two groups. The independent t test was applied at a confidence level of95%.·RESULTS： The far and near FC amplitudes and far FD amplitudes were lower in the AHP group（the far FC amplitudes： break point 13.6±5.4~△, recovery point 8.7±5.4~△.The near FC amplitudes： break point 14.5 ±7.3~△, recovery point 10. 3 ± 5. 1~△. The far FD amplitudes ： break point3.9±2.7~△, recovery point 2.6±2.3~△） compared with those in the normal group（the far FC amplitudes： break point19.1 ±6.2△, recovery point 12.4 ±4.5~△. The near FC amplitudes： break point 22.3 ±8.0~△, recovery point 16.1 ±5.7~△. The far FD amplitudes： break point 7.0 ±2.1~△,recovery point 4.6 ±1.9~△）. Other tests presented no statistically significant differences.·CONCLUSION： An association between the reduced FC and FD amplitudes and the AHP in children when watching TV is proposed in the study. This kind of AHP is considered to be an anomalous manifestation which appears in a part of puerile patients of fusional vergence dysfunction.

Binocular Vision Positioning Method for Safety Monitoring of Solitary Elderly

In nowadays society,the safety of the elderly population is becoming a pressing concern,especially for those who live alone.There might be daily risks such as accidental falling or treatment attack on them.Aiming at these problems,indoor positioning could be a critical way to monitor their states.With the rapidly development of the imaging techniques,wearable and portable cameras are very popular,which could be set on human individual.And in view of the advantages of the visual positioning,the authors propose a binocular visual positioning algorithm to real-timely locate the elderly indoor.In this paper,the imaging model has been established with the corrected image data from the binocular camera;then feature extraction has been completed to provide reference to adjacent image matching based on the binary robust independent elementary feature(BRIEF)descriptor,finally the camera movement and the states of the elderly have been estimated to distinguish their falling risk.In the experiments,the real-sense D435i sensors were adopted as the binocular cameras to obtain indoor images,and three experimental scenarios have been carried out to test the proposed method.The results show that the proposed algorithm can effectively locate the elderly indoor and improve the real-time monitoring capability.

Binocular Vision Object Positioning Method for Robots Based on Coarse-fine Stereo Matching

In order to improve the low positioning accuracy and execution efficiency of the robot binocular vision,a binocular vision positioning method based on coarse-fine stereo matching is proposed to achieve object positioning.The random fern is used in the coarse matching to identify objects in the left and right images,and the pixel coordinates of the object center points in the two images are calculated to complete the center matching.In the fine matching,the right center point is viewed as an estimated value to set the search range of the right image,in which the region matching is implemented to find the best matched point of the left center point.Then,the similar triangle principle of the binocular vision model is used to calculate the 3D coordinates of the center point,achieving fast and accurate object positioning.Finally,the proposed method is applied to the object scene images and the robotic arm grasping platform.The experimental results show that the average absolute positioning error and average relative positioning error of the proposed method are 8.22 mm and 1.96%respectively when the object's depth distance is within 600 mm,the time consumption is less than 1.029s.The method can meet the needs of the robot grasping system,and has better accuracy and robustness.

A Fast Moving Target Detection Tracking and Trajectory Prediction System for Binocular Vision

Aiming at achieving complex moving targets perception,this paper designs a novel fusion-information detection and tracking system for moving targets.The system includes three modules:target detection,target tracking and trajectory prediction.The target detection module can detect fast moving objects which can be used as a template.The target tracking module tracks the object and records its historical position.Finally,the trajectory prediction module can predict the trajectory of the moving object based on the historical position.After verification by the table tennis detection tracking and prediction binocular vision system,the system has high accuracy and speed in detection and tracking,and can basically meet the actual application needs.

Tractor path tracking control based on binocular vision

In the process of field operation management,determining how to accurately realize crop row identification and path tracking control is an essential part of tractor automatic navigation.According to the linear operation in the process of cotton field management,the tractor path tracking control system was designed based on binocular vision and the pure pursuit model.A new crop row detection method based on the Census transform and the PID control algorithm with dead zone were used.First,the upper computer software was developed by C++with the functions of parameter setting and image acquisition and processing.Second,an automatic steering controller was developed based on microprocessor MC9S12XS128 of Freescale.The control program was developed based on modular design using CodeWarrior during development of the PID-based automatic steering control strategy.Finally,a field experiment platform of tractor path tracking control was built,and field experiments under the actual cotton were conducted.The optimal visibility distance was determined by several previous experiments.When the tractor tracks the path with the optimal visibility distance in the growth environment of actual cotton crops,the mean absolute deviation of course angle was 0.95°,and the standard deviation was 1.26°;the mean absolute deviation of lateral position was 4.00 cm,and the standard deviation was 4.97 cm;the mean absolute deviation of front wheel angle was 2.99°,and the standard deviation was 3.67°.The experimental results show that(1)the crop row detection method based on Census transform can identify the crop line and plan the navigation path well,and(2)the tractor path tracking control system based on binocular vision has good stability and high control precision;thus,the control systemcan realize the automatic path tracking control of cotton line operation and meets the agricultural requirements of cotton field operation management.

Minimum energy optimal external torque control of human binocular vision

In this paper,we consider eyes from the human binocular system,that simultaneously gaze on stationary point targets in space,while optimalal skipping from one target to the next,by rotaing their individual gaze drecton.The head is assume fixed on the torso and the rotaing gaze direction of the two eyes are assumed restricted to pass through a point in the visual space.It is further assumed that,individullly the rotations of the two eyes satisfy the well known Listing's law.We formulate and study acombined optimal gaze rotation for the two eyes,by constructing a single Riemanmian metric,on the asociaced parameter space.The goal is to optimally rotate so that the convergent gaze changes between two pre-specified target points in a finite time interval[0,1].The cost function we choose is the total energy,measured by the L2?norm,of the six extenal torques on the binocular system.The torque functions are synthesized by solving an associated*two-point boundary value problem.The paper demonstrates,via simulation,the shape of the optimal gaze trajectory of the focused point of the bin-ocular system.The Euclidean distance between the initial and the final point is compared to the arc:length of the optimal trajectory.The consumed energy.is computed for diferent eye movement chores and discussed in the paper.Via simulation we observe that certain eye movement maneuvers are energy fficicnt and demonstrate that the optimal external torque is a linear function in time.We also explore and conclude that spitting an arbitry opimal eye movement into optimal vergence and version components is not energy fficient although this is how the human oculomotor control seems to operate.Opimal gaze tajectories and opimal extermal torque functions reported in this paper is new.

Measurement method for cluster warhead's dispersion area based on binocular stereo vision technique

Cluster warhead has become the main ammunition of gun,rocket projectile and missile and it has been widely equipped in almost every country.More and more attention is paid to the damage effect of cluster warhead.The size of the dispersion area of cluster warhead is the main standard by which the damage effect of cluster warhead is estimated.The practical method of measuring the dispersion area was developed based on binocular stereo vision measurement theory.The calibration principle of the binocular stereo vision cameras was studied.The matching algorithm that relies on the gradient fields of the neighborhood of a pixel has been used to obtain the spatial information of matched points by acquiring apair of corresponding points in the left and right images of binocular cameras.The 3Dpositions of the flying path of cluster warhead were calculated.The umbrella that is similar to the dispersion track of static explosive cluster warhead was applied in the experiment to get the projection area of the umbrella on the ground.Experiment results verify the feasibility of the proposed method.

Monitoring driver attention distraction with binocular vision

Driver attention distraction(DAD)is a typical artificial factor traffic accident,and DAD monitoring can improve driving security.In this study,a method was developed for accurate DAD monitoring based on binocular vision.A binocular vision system was built,and camera parameters of the system were calibrated based on Open CV.In the method,the driver’s facial image is obtained by using active infrared imaging technology and preprocessed to locate the eye positions.The connected component labeling algorithm for binary images is used to pinpoint the eye locations.The characteristic information of the eye pupils is extracted with the least-squares ellipse fitting algorithm,and the characteristic information of the Purkinje image is obtained with the Harris corner detection algorithm.A DAD warning model based on the binocular vision system was established to evaluate the attention state of the driver.

Accuracy study of a binocular-stereo-vision-based navigation robot for minimally invasive interventional procedures

BACKGROUND Medical robot is a promising surgical tool,but no specific one has been designed for interventional treatment of chronic pain.We developed a computed tomography-image based navigation robot using a new registration method with binocular vision.This kind of robot is appropriate for minimal invasive interventional procedures and easy to operate.The feasibility,accuracy and stability of this new robot need to be tested.AIM To assess quantitatively the feasibility,accuracy and stability of the binocularstereo-vision-based navigation robot for minimally invasive interventional procedures.METHODS A box model was designed for assessing the accuracy for targets at different distances.Nine(three sets)lead spheres were embedded in the model as puncture goals.The entry-to-target distances were set 50 mm(short-distance),100 mm(medium-distance)and 150 mm(long-distance).Puncture procedure was repeated three times for each goal.The Euclidian error of each puncture was calculated and statistically analyzed.Three head phantoms were used to explore the clinical feasibility and stability.Three independent operators conducted foramen ovale placement on head phantoms(both sides)by freehand or under the guidance of robot(18 punctures with each method).The operation time,adjustment time and one-time success rate were recorded,and the two guidancemethods were compared.RESULTS On the box model,the mean puncture errors of navigation robot were 1.7±0.9 mm for the short-distance target,2.4±1.0 mm for the moderate target and 4.4±1.4 mm for the long-distance target.On the head phantom,no obvious differences in operation time and adjustment time were found among the three performers(P>0.05).The median adjustment time was significantly less under the guidance of the robot than under free hand.The one-time success rate was significantly higher with the robot(P<0.05).There was no obvious difference in operation time between the two methods(P>0.05).CONCLUSION In the laboratory environment,accuracy of binocular-stereo-vision-based navigation robot is acceptable for target at 100 mm depth or less.Compared with freehand,foramen ovale placement accuracy can be improved with robot guidance.

Measuring Propeller Blade Width Using Binocular Stereo Vision

Propeller blade width measurement has been extensively studied in the past using direct and indirect methods, and it plays a great role in determining the quality of the finished products. It has surveyed that previous techniques are usually time-consuming and erroneous due to a large number of points to be processed in blade width measurement. This paper proposes a new method of measuring blade width using two images acquired from different viewpoints of the same blade. And a new feature points matching approach for propeller blade image is proposed in stereo vision measurement. Based on these, pixel coordinates of contour points of the blade in two images are extracted and converted to real world coordinates by image algorithm and binocular stereo machine vision theory. Then, from the real world coordinates, the blade width at any position can be determined by simple geometrical method.

Research on Extraction of Bottom of Shoe Pattern Based on Binocular Stereo Vision

In order to quickly and efficiently get the information of the bottom of the shoe pattern and spraying trajectory, the paper proposes a method based on binocular stereo vision. After acquiring target image, edge detection based on the canny algorithm, the paper begins stereo matching based on area and characteristics of algorithm. To eliminate false matching points, the paper uses the principle of polar geometry in computer vision. For the purpose of gaining the 3D point cloud of spraying curve, the paper adopts the principle of binocular stereo vision 3D measurement, and then carries on cubic spline curve fitting. By HALCON image processing software programming, it proves the feasibility and effectiveness of the method

Hawk‐eye‐inspired perception algorithm of stereo vision for obtaining orchard 3D point cloud navigation map

The binocular stereo vision is the lowest cost sensor for obtaining 3D information.Considering the weakness of long‐distance measurement and stability,the improvement of accuracy and stability of stereo vision is urgently required for application of precision agriculture.To address the challenges of stereo vision long‐distance measurement and stable perception without hardware upgrade,inspired by hawk eyes,higher resolution perception and the adaptive HDR(High Dynamic Range)were introduced in this paper.Simulating the function from physiological structure of‘deep fovea’and‘shallow fovea’of hawk eye,the higher resolution reconstruction method in this paper was aimed at ac-curacy improving.Inspired by adjustment of pupils,the adaptive HDR method was proposed for high dynamic range optimisation and stable perception.In various light conditions,compared with default stereo vision,the accuracy of proposed algorithm was improved by 28.0%evaluated by error ratio,and the stability was improved by 26.56%by disparity accuracy.For fixed distance measurement,the maximum improvement was 78.6%by standard deviation.Based on the hawk‐eye‐inspired perception algorithm,the point cloud of orchard was improved both in quality and quantity.The hawk‐eye‐inspired perception algorithm contributed great advance in binocular 3D point cloud recon-struction in orchard navigation map.

RANGE ACQUISITION IN BINOCULAR 3-D COMPUTER VISION USING EDGE-BASED HIERARCHICAL MATCHING

This paper deals with a binocular 3-D computer vision system based on the hierarchicalmatching of edge features, Frei and Chen operator is used to extract the edge. The averagegradients of an image obtained by two isotropic operators are non-equal quantized andthresholded in an angle, Edge features are extracted after passing a preemphasis transferfunction which can equalize, the noise affection. Binary edge images are decomposed into apyramid structure which is stored and searched using llliffe’s location method. Corre-sponding points are used to determine the range data using triangulation based on an improvedTrivedi’s formula. In calibration the authors set the optical axes of the two cameras parallelto simplify the calculation, A 3 rd order Householder transform is used to solve the compati-ble coupled equations.

Experiment Research on Binocular Perceptual Characteristics around Peripheral Vision for Development of Head Mounted Display with Wide View

The head mounted display （HMD） is widely used in virtual reality technology. In common HMD, however, the binocular disparity is set to an equal fixed value in the entire range of view. Such HMD systems have several shortcomings when used for wide views. In this study, in order to realize a natural stereo sensation of HMD with wide view, we measure the characteristics of binocular stereo perception and binocular light perception. Results show that both the stereoacuity and light sensitivity decrease as the retina＇s eccentricity increases from fovea to periphery. However, the decrease of the stereoacuity is more rapid than that of the light sensitivity. These results suggest that the binocular disparity at the peripheral field should be small, otherwise double images would be observed instead of a stereo view. Based on the results we develop a relative binocular stereoacuity model which can be applied for the design of HMD systems with wide view.

基于改进YOLOv8和GMM图像点集匹配的双目测距方法

针对无人塔吊系统的研究需求,提出一种基于改进YOLOv8和GMM图像点集匹配的双目测距方法,对驾驶室外环境中的塔吊吊钩进行检测识别并测距。通过双目摄像头进行图像采集,引入FasterNet骨干网络和Slim-neck颈部连接层,对YOLOv8目标检测算法进行改进,有效检测画面中的塔吊吊钩并获取检测框的二维坐标信息;采用局部敏感哈希方法,并融合分阶段匹配策略,提升GMM图像点集匹配模型的匹配效率,针对检测框中的塔吊吊钩,进行特征点匹配;最后通过双目相机三角测量原理计算得出塔吊吊钩的深度信息。实验结果表明,改进后的YOLOv8算法与原算法相比,精确率P提高了2.9%,平均精度AP50提高了2.2%,模型复杂度降低了10.01 GFLops,参数量减少了3.37 M,在提升检测精度的同时实现了模型的轻量化。改进后的图像点集匹配算法与原算法相比,各个指标表现出更加良好的鲁棒性。最后在工程现场对塔吊吊钩进行识别与测距,误差可接受范围内有效完成了塔吊吊钩的检测识别与测距任务,验证了本方法的可行性。

基于单激光束信息的掘锚装备视觉定位方法研究

煤矿井下掘锚装备智能化是改善行业采掘失衡问题的关键,而掘锚装备的精确定位是实现其智能化的前提。与其他传统定位方法相比,基于视觉的位姿测量方法以其无接触、无累计误差的优势在煤矿井下得到了初步的应用。针对目前煤矿井下掘进工作面掘锚装备视觉定位方法存在的合作标靶结构复杂、标定繁琐的问题,结合掘进工作面原有激光指向仪特征,提出一种基于单激光束信息的掘锚装备视觉定位方法。该方法通过分析激光指向仪光斑及光束图像特征,提出了一种基于二维反正切函数拟合的激光光斑中心提取方法和基于Hough直线检测的激光束中心线提取方法,构建了基于点线特征的双目视觉位姿解算模型,得出了掘锚装备在巷道中的实时位姿。最后,为了验证提出的特征提取方法和视觉定位方法的可行性和准确性,在实验室模拟掘进工作面工况环境搭建平台进行了试验。结果表明:基于矿用激光指向仪信息的掘锚装备视觉定位方法具有较高的位姿测量精度。在50 m的测试范围内,机身位置在巷道坐标系下沿X轴、Y轴和Z轴的平均测量误差分别为25.44、58.64、31.08 mm,其最大误差分别为55.16、127.39、63.57 mm;机身姿态在巷道坐标系下的俯仰角、偏航角和横滚角的平均测量误差分别为0.22°、0.22°、0.41°,其最大误差分别为0.29°、0.37°、0.58°。满足煤矿井下巷道施工的定位精度要求。

基于深度学习的巡检机器人避障轨迹自动控制系统设计

为了提高巡检机器人在复杂环境下的避障能力,使机器人能够安全地完成巡检任务,设计基于深度学习的巡检机器人避障轨迹自动控制系统;设计由CCD传感器、信号处理芯片等设备组成的工业智能视觉CCD相机,基于FPGA和USB2.0的视频采集卡传输采集数据,完成硬件部分的设计;在软件设计中,对采集的图像实施目标分割、双目目标匹配等预处理,通过对摄像头实施双目视觉标定获取障碍物空间位置三维信息,基于深度学习中的CRNN设计机器人自主避障规划网络模型,并设计模糊轨迹控制器,实现避障中的轨迹自动控制;系统测试结果表明,设计系统最终成功避开了3个动态障碍物,最大轨迹控制误差的最大值为1.45°,最小轨迹控制误差的最大值为0.62°,动态避障巡检速度始终在3.5 m/s左右,表现出了精准而稳定的轨迹控制效果。

基于双目深度筛选的ORB-SLAM3算法

针对ORB-SLAM3算法中特征点存在易丢失、精度低,进而导致双目在复杂场景下运动轨迹误差大的问题,本文设计了一种改进的ORB-SLAM3算法。首先,在ORB特征匹配算法中引入自适应角点检测技术,增加特征点的采集数量,并采用光流法跟踪图像特征,提高关键帧的创建成功率;其次,以特征点为中心,作区域搜索,提高实时性;然后,采用双向左右一致性检验筛选最优视差,应用Prosac算法去除误匹配点对;最后,结合深度信息对关键帧进行筛选,提高关键帧的质量,优化相机位姿。采用KITTI和EuRoc数据集进行了试验,验证了改进算法在绝对轨迹误差上具有良好的优化效果。

基于双目视觉的车前行人检测方法研究

当前的汽车安全辅助驾驶和无人驾驶汽车是图像领域的研究热点,针对汽车在启动或行驶时车前存在行人可能导致的安全问题,着重研究了基于双目视觉的车前行人检测方法。进行了双目相机的相机标定和立体标定;通过改进后半全局立体匹配算法获取深度图,确定车前行人所处位置的感兴趣区域(Region of Interest,ROI),剔除冗余的背景信息;分割并提取了图像的降维梯度直方图(Histogram of Gradients,HOG)特征信息;将特征输入到支持向量机(Support Vector Machine,SVM)分类器训练,检测并标记出车前的行人目标。实验证明,所提算法对车前场景下的动态行人可以更为有效地检测,具备更优的检率精度、时效性和鲁棒性。