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

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.

基于双目立体视觉的多分辨率图像匹配方法研究

在双目立体视觉系统中,面对复杂场景时噪声会损害图像特征,增加提取难度,导致匹配精度和鲁棒性下降。因此,文中提出基于双目立体视觉的多分辨率图像匹配方法,旨在从不同尺度图像中有效获取信息并实现高精度匹配。该方法利用双目立体视觉模型的双目旋转相机扫描目标并进行成像,根据内、外空间标定提升双目旋转相机的位置精度,保证目标的多分辨率成像效果;将其输入金字塔立体匹配网络中,通过网络中的类金字塔多空洞卷积操作提取双目图像特征,在此基础上,基于可变卷积增强其纹理特征细节;结合细粒度特征和互注意力机制完成双目图像匹配。测试结果显示,空间标定后,左、右两个相机的成像误差最小值分别为0.6 Pixel和0.4 Pixel;匹配点坐标偏差均值和坐标偏差方差值分别低于0.012和0.011,匹配效果良好。

基于人工神经网络和机器视觉的棉花分拣系统研究

首先,介绍了卷积神经网络的原理,并基于双目视觉搭建了棉花分拣视觉系统;然后,基于3×3窗口、Sobel和Hough等算法,实现了棉花图像的边缘检测和特征提取功能;最后,基于卷积神经网络对棉花图像进行特征提取和优劣分类,并利用双目视觉对识别的棉花进行空间定位。实验结果表明:棉花分拣系统的准确率为96.50%,能够有效地满足实际应用的要求。

基于双目视觉技术的茶叶嫩芽定位方法研究

进一步提升茶叶嫩芽定位的准确性及茶叶嫩芽采摘的作业效率,选取双目视觉技术作为切入点,针对其识别、定位、采摘等环节展开设计研究。考虑茶叶嫩芽采摘的基础特征和双目视觉技术的应用条件,合理搭建双目视觉模型,选用立体匹配的核心定位算法,完成茶叶嫩芽的定位方法与采摘功能优化,并布置相应的试验机构,展开定位采摘验证试验。结果表明:基于双目视觉技术的茶叶嫩芽定位方法应用具有显著的优越性,较普通定位方法而言,识别误匹配率可降低至4.01%,平均漏采率为3.20%,嫩芽采摘完整率达93.40%,可以很好地促进茶叶嫩芽的后续处理加工,是采摘茶叶嫩芽的品质化的重要基础保障。

REAL-TIME STEREO MATCHING ALGORITHM IN PHOTODYNAMIC THERAPY BINOCULAR SURVEILLANCE SYSTEM FOR PORT WINE STAIN

A stereo matching algorithm based on the epipolar line constraint is designed to meet the real-time and the accuracy requirements. The algorithm is applied to photodynamic therapy binocular surveillance system for port wine stain （PWS） when it monitors the position of the treatment region. The corner matching based on Hu moments is used to calculate the fundamental matrix of the binocular vision system. Experimental results are in agreement with the theoretical calculation.

基于双目视觉和改进YOLOv8n的火灾检测及测距方法

针对火灾检测出现的漏检误检、模型参数量大及定位困难的问题,基于双目视觉和改进YOLOv8n提出了一种轻量化火灾检测及测距方法.通过双目相机拍摄图片,使用改进的检测算法YOLOv8n-AEM和现有的测距算法SGBM进行检测和测距.首先,在主干网络中引入可变核卷积AKConv和EMA注意力机制,通过构建不规则卷积核有效提取火灾的特征;然后,在颈部网络中构建C2f-SCConv模块,通过特征重组降低模型参数,提高检测速度;其次,基于最小点距离改进损失函数,解决火源与光源重叠导致的漏检与误检问题;最后,增加小目标检测头,提高对小火苗的检测能力.实验结果表明,改进后的检测算法P、R、mAP分别为83.6%、76.4%、83.6%,分别提高了2.5%、3.6%、4.8%;参数量和模型大小分别为2.54 M和5.1 MB,分别降低了15.3%和15%;测距精度误差不超过2.5%,证明改进的方法能准确完成火灾的检测及测距.

基于EVision的双目视觉系统的设计与实现

设计和开发了一个排爆机器人的双目立体视觉系统。该系统使用Matlab7.0和机器视觉软件EVision6.2的EasyMultiCam进行图像捕获并和EasyMath模式匹配库进行图像特征匹配,能实时捕获排爆机器人周围的图像信息、进行摄像机标定、图像预处理、立体图像匹配、求取可疑目标物的特征点的立体坐标,并把图中实时显示在控制台上,控制排爆机器人准确地抓取可疑目标物。该机器人视觉系统成功的抓取实验,表明了它在精度上能够满足排爆机器人的项目要求。