三维形貌柔性测量系统标定方法及验证

为了避免机器人模型误差对三维形貌柔性测量系统手眼标定的影响,对手眼关系的标定方法进行了研究。提出了一种融合特征点拟合的手眼标定方法。将三维形貌扫描仪安装在工业机器人末端搭建三维形貌柔性测量系统。标定时,首先利用激光跟踪仪对工业机器人末端法兰盘坐标系进行测量,得到两者转换关系;然后,利用三维形貌扫描仪和激光跟踪仪对空间固定的特征点组进行测量,利用特征点约束和基于罗德里格矩阵的算法求解两者转换关系即可间接地求解出手眼关系。基于ATOS三维扫描仪、安川HP20D机器人和API公司生产的激光跟踪仪进行了手眼标定实验,并进行了精度验证。结果表明:标定后的三维形貌柔性测量系统,其重复性测量精度(3σ)不超过0.1 mm,长度测量精度的均方根误差在0.2 mm以内,点云拼接精度优于±0.7 mm。该方法有效避免了传统手眼标定过程中会引入机器人模型误差的问题,在求解手眼关系解时采用了线性的解法,并且适用于三维形貌柔性测量系统。     

Single-camera panoramic stereo system model based on skew ray tracing

This study integrates panoramic imaging and stereo vision theory to propose an innovative 3D optical positioning method for single-camera panoramic stereo imaging systems. The conventional single-viewpoint theory based on pinhole modeling is replaced by a skew ray tracing methodology to establish the geometrical relationships of object and image. An analytical model of a single-CCD panoramic stereo imaging system is then established by adopting a catadioptric imaging system, a single-CCD stereo panoramic vision system and the presented skew ray camera calibration method.     

Single-camera active stereo vision system using fiber bundles

We propose an approach for realizing 3D reconstruction in small field of view or some extreme environments. We combine the stereo vision and the structured light technologies and change the traditional ways of applying them by employing two fiber bundles. The processes of calibration and 3D reconstruction are also introduced. Experiments are performed to verify the feasibility and effectiveness of our proposed approach.     

基于四目系统的真实场景三维建模

为实现敦煌莫高窟文化遗产数字化保护,设计了一套基于四目系统的真实场景三维建模方法。针对双目立体视觉系统特征点匹配精度不高的问题,构建了一种四目立体视觉系统,并设计了与之相适应的高精度立体匹配策略,运用四目系统的冗余设计和自检验功能,可以获得高精度的空间点云数据。针对Delaunay三角化结果中不相关目标的错误连接问题,增加三角形边长分别在图像坐标系和世界坐标系中的约束条件,抑制错误三角形,该条件可根据点云数据分布特征自适应获取。该系统已被运用到莫高窟第172窟的三维重建中。结果表明:该系统可以重建多目标、深度变化大的复杂场景,172窟的有效点云为41 649点,三维建模时间约为0.5 h。     

基于网格点投影灰度相似性的三维重建新方法

基于双目立体视觉的三维重构是计算机视觉技术的主要内容之一,在机器人视觉导航、航空测绘、医学成像和工业检测等很多领域都有广泛的应用.提出一种基于网格点投影灰度相似性的双日立体视觉的三维重建新方法.首先将被测物体所在的世界坐标系划分成问距卡日等的矩形网格,将网格节点作为潜在的物点投影到左右图像坐标系上,然后根据不同深度的空间点在两幅图像上相应的灰度相似性来判断被测物体在三维空间中的深度信息.通过Matlab平台下的仿真实验证明了本方法的三维重建效果和计箅效率都要优于传统方法.与传统的图像匹配方法相比,具有算法简单、速度快、精度高、且不受摄像装置非线性畸变影响的优点.     

Recent advances in 3D SEM surface reconstruction

The scanning electron microscope (SEM), as one of the most commonly used instruments in biology and material sciences, employs electrons instead of light to determine the surface properties of specimens. However, the SEM micrographs still remain 2D images. To effectively measure and visualize the surface attributes, we need to restore the 3D shape model from the SEM images. 3D surface reconstruction is a longstanding topic in microscopy vision as it offers quantitative and visual information for a variety of applications consisting medicine, pharmacology, chemistry, and mechanics. In this paper, we attempt to explain the expanding body of the work in this area, including a discussion of recent techniques and algorithms. With the present work, we also enhance the reliability, accuracy, and speed of 3D SEM surface reconstruction by designing and developing an optimized multi-view framework. We then consider several real-world experiments as well as synthetic data to examine the qualitative and quantitative attributes of our proposed framework. Furthermore, we present a taxonomy of 3D SEM surface reconstruction approaches and address several challenging issues as part of our future work.     

基于计算机视觉的非朗伯表面三维重构

基于计算机视觉的三维重构方法已经广泛应用在各行各业中。目前的三维重构研究主要针对不透明的朗伯表面,且已经比较成熟,但对非朗伯表面仍然面临诸多问题。而实际场景中的物体表面大多是非朗伯表面,因而,随着实际应用的推广,非朗伯表面的三维重构问题在计算机视觉领域越来越受到关注。虽然本现状研究不能完全涵盖针对非朗伯表面三维重构的所有方法,但它包涵了三维重构每个步骤中的各种典型方法。文中按照图像获取过程中的照明方式和重构原理对现有方法进行了分类,并逐类进行了介绍。由于不存在公共测试网络平台和带有标准视差的非朗伯表面立体图像集,因而,很难对各种算法的计算效率和匹配质量进行比较,文中主要对非朗伯表面的现有三维重构方法的原理、特点、适用范围和最新研究方向进行了介绍,对非朗伯表面三维重构的现有问题和发展前景进行了讨论。     

昆虫飞行中翅膀序列图像特征匹配方法

分析了翅膀外形结构特点以及在序列图像中翅膀边缘特征的变化,提出了基于拓扑变换的几何相对位置不变的约束方法,对翅膀边缘特征进行分区域匹配去掉虚假匹配点;然后利用极线约束实现精确匹配,最终得到在运动过程中翅膀的三维形貌。提出的约束匹配方法不仅有效地剔除了虚假匹配,同时也极大地减小了特征匹配的运算量。实际应用证明此约束匹配方法是较为有效的。     

Three-dimensional imaging and visualization of partially occluded objects using axially distributed stereo image sensing

In this Letter, we propose a multiperspective three-dimensional (3D) imaging system using axially distributed stereo image sensing. In this proposed method, the stereo camera is translated along its optical axis and multiple axial elemental image pairs for a 3D scene are collected. The captured elemental images are reconstructed in 3D using a computational reconstruction algorithm based on ray back-projection. The proposed method is applied to partially occluded object visualization. Optical experiments are performed to verify the approach.     

3D laser scanner system using high dynamic range imaging

Because of its high measuring speed, moderate accuracy, low cost and robustness in the industrial field, 3D laser scanning has been widely used in a variety of applications. However, the measurement of a 3D profile of a high dynamic range (HDR) brightness surface such as a partially highlighted object or a partial specular reflection remains one of the most challenging problems. This difficulty has limited the adoption of such scanner systems. In this paper, an optical imaging system based on a high-resolution liquid crystal on silicon (LCoS) device and an image sensor (CCD or CMOS) was built to adjust the image's brightness pixel by pixel as required. The radiance value of the image captured by the image sensor is constrained to lie within the dynamic range of the sensor after an adaptive algorithm of pixel mapping between the LCoS mask plane and image plane through the HDR imaging system is added. Thus, an HDR image was reconstructed by the LCoS mask and the CCD image on this system. The significant difference between the proposed system and a traditional 3D laser scanner system is that the HDR image was used to calibrate and calculate the 3D profile coordinate. Experimental results show that HDR imaging can enhance 3D laser scanner system environmental adaptability and improve the accuracy of 3D profile measurement.     

Robust geometric,phase and colour structured light projection system calibration

This paper introduces a new comprehensive procedure for both geometric and colour calibration of structured light system. In order to perform both geometric and colour calibration procedure, a new calibration artifact is proposed. The intrinsic and extrinsic parameters of projector and camera are estimated by using an extended pinhole camera model with a tangential and radial distortion. Camera image plane coordinates are obtained by extracting features from images of a calibration artifact. Projector image plane coordinates are calculated on the basis of continuous phase maps obtained from a fringe pattern phase reconstruction procedure. In order to stereo calibrate camera-projector system, pairs of corresponding image plane points are calculated with subpixel accuracy. In addition, one of three pattern views is used in colour calibration. RGB values of a colour field pattern detected by camera and their reference values are compared. This comparison leads to derivation of a colour transformation matrix. The performance of the proposed method is tested by measuring plane, sphere and distance reference. Also 360 degrees complex object 3D model from a set of measurements is obtained. Residual mean errors for all tests performed are calculated.     

Calibration for stereo vision system based on phase matching and bundle adjustment algorithm

Calibration for stereo vision system plays an important role in the field of machine vision applications. The existing accurate calibration methods are usually carried out by capturing a high-accuracy calibration target with the same size as the measurement view. In in-situ 3D measurement and in large field of view measurement, the extrinsic parameters of the system usually need to be calibrated in real-time. Furthermore, the large high-accuracy calibration target in the field is a big challenge for manufacturing. Therefore, an accurate and rapid calibration method in the in-situ measurement is needed. In this paper, a novel calibration method for stereo vision system is proposed based on phase-based matching method and the bundle adjustment algorithm. As the camera is usually mechanically locked once adjusted appropriately after calibrated in lab, the intrinsic parameters are usually stable. We emphasize on the extrinsic parameters calibration in the measurement field. Firstly, the matching method based on heterodyne multi-frequency phase-shifting technique is applied to find thousands of pairs of corresponding points between images of two cameras. The large amount of pairs of corresponding points can help improve the accuracy of the calibration. Then the method of bundle adjustment in photogrammetry is used to optimize the extrinsic parameters and the 3D coordinates of the measured objects. Finally, the quantity traceability is carried out to transform the optimized extrinsic parameters from the 3D metric coordinate system into Euclid coordinate system to obtain the ultimate optimal extrinsic parameters. Experiment results show that the procedure of calibration takes less than 3 s. And, based on the stereo vision system calibrated by the proposed method, the measurement RMS (Root Mean Square) error can reach 0.025 mm when measuring the calibrated gauge with nominal length of 999.576 mm.     

Improve a 3D distance measurement accuracy in stereo vision systems using optimization methods’ approach

This paper presents a 3D distance measurement accuracy improvement for stereo vision systems using optimization methods A Stereo Vision system is developed and tested to identify common uncertainty sources. As the optimization methods are used to train a neural network, the resulting equation can be implemented in real time stereo vision systems. Computational experiments and a comparative analysis are conducted to identify a training function with a minimal error performance for such method. The offered method provides a general purpose modelling technique, attending diverse problems that affect stereo vision systems. Finally, the proposed method is applied in the developed stereo vision system and a statistical analysis is performed to validate the obtained improvements.     

基于目标运动的复眼式双目视觉测距法

昆虫（螳螂）复眼利用目标的动态差异实现立体视觉,具有视场大、计算简单、实时性高等特点,是立体视觉研究的新方向。为实现复眼立体视觉在机器人视觉导航中的应用,根据复眼结构以及信息处理机制,提出并研究了环形光电传感器的目标快速检测与定位方法。首先,搭建了基于60个光电二极管的等6°夹角分布式环形传感器,形成具有360°视场的环形仿生复眼;其次,建立了基于光流原理的运动目标方位角检测模型,采用傅里叶拟合法实现了方位角检测模型的优化,实现了运动目标方位角与目标距离大视野范围内的简单、快速检测。实验结果表明:1）可实现距离375 mm范围内运动速度为30 mm/s的目标方位角实时检测,测量误差在2°范围内;2）基于目标方位角检测模型,可实现双目阵列传感器在300 mm×375 mm视野重叠区域范围内、平均测量误差在10 mm范围内的立体视觉测距。基于光流的运动目标方位角检测模型可用于实现对运动目标空间位置的动态实时检测,在运动检测、视觉导航等领域具有广泛的应用前景。     

利用反射全息实现计算全息三维显示

计算全息和光学全息都可应用于三维显示,但各有自己的优势和缺陷.将计算全息和光学反射全息相结合,可以突破光学全息对记录物体的限制,进行虚拟物体或自然场景的全息图的制作,同时可以实现白光再现.本文首先用三维扫描仪获得实际物体的三维数据,用"点云算法"模拟得到其菲涅耳全息图透射率数据,采用计算全息打印机将其输出于全息记录介质,得到可光学再现的菲涅耳计算全息图H1.然后将H1作为光学全息的记录物体进行反射全息记录,将平面全息转化为体全息,实现了计算全息白光再现.     

利用反射全息实现计算全息三维显示

计算全息和光学全息都可应用于三维显示,但各有自己的优势和缺陷.将计算全息和光学反射全息相结合,可以突破光学全息对记录物体的限制,进行虚拟物体或自然场景的全息图的制作,同时可以实现白光再现.本文首先用三维扫描仪获得实际物体的三维数据,用"点云算法"模拟得到其菲涅耳全息图透射率数据,采用计算全息打印机将其输出于全息记录介质,得到可光学再现的菲涅耳计算全息图H₁.然后将H₁作为光学全息的记录物体进行反射全息记录,将平面全息转化为体全息,实现了计算全息白光再现.     

Probability analysis of position errors using uncooled IR stereo camera

This paper analyzes the random phenomenon of 3D positions when tracking moving objects using the infrared (IR) stereo camera, and proposes a probability model of 3D positions. The proposed probability model integrates two random error phenomena. One is the pixel quantization error which is caused by discrete sampling pixels in estimating disparity values of stereo camera. The other is the timing jitter which results from the irregular acquisition-timing in the uncooled IR cameras. This paper derives a probability distribution function by combining jitter model with pixel quantization error. To verify the proposed probability function of 3D positions, the experiments on tracking fast moving objects are performed using IR stereo camera system. The 3D depths of moving object are estimated by stereo matching, and be compared with the ground truth obtained by laser scanner system. According to the experiments, the 3D depths of moving object are estimated within the statistically reliable range which is well derived by the proposed probability distribution. It is expected that the proposed probability model of 3D positions can be applied to various IR stereo camera systems that deal with fast moving objects.     

一种目标空间运动分析系统

针对运动目标空间定位问题,将立体视觉技术与单视频序列下的运动目标检测相结合,设计了一种目标空间运动分析系统,实现目标的空间定位,扩展了单视频序列运动目标检测课题的应用范围。针对从单目向多目过渡过程中面临的问题,从硬件上提出了相应的解决方案,将立体镜头与高速相机相结合,克服了芯片一致性、相机同步、运动拖影等影响。由于立体像对源于同一帧图像,所以可以直接使用传统单序列运动目标检测方法获取运动掩模。使用该空间运动分析系统在光照充足的室外条件下进行单一目标的自由落体和斜坡运动2组实验,实验结果表明:该系统运行稳定,实现了运动目标的空间位置分析功能,1 m范围内,定位绝对误差小于0.01 m。     

An omnidirectional 3D sensor with line laser scanning

An active omnidirectional vision owns the advantages of the wide field of view (FOV) imaging, resulting in an entire 3D environment scene, which is promising in the field of robot navigation. However, the existing omnidirectional vision sensors based on line laser can measure points only located on the optical plane of the line laser beam, resulting in the low-resolution reconstruction. Whereas, to improve resolution, some other omnidirectional vision sensors with the capability of projecting 2D encode pattern from projector and curved mirror. However, the astigmatism property of curve mirror causes the low-accuracy reconstruction. To solve the above problems, a rotating polygon scanning mirror is used to scan the object in the vertical direction so that an entire profile of the observed scene can be obtained at high accuracy, without of astigmatism phenomenon. Then, the proposed method is calibrated by a conventional 2D checkerboard plate. The experimental results show that the measurement error of the 3D omnidirectional sensor is approximately 1 mm. Moreover, the reconstruction of objects with different shapes based on the developed sensor is also verified.     

Large depth-of-view portable three-dimensional laser scanner and its segmental calibration for robot vision

A portable 3D laser scanning system has been designed and built for robot vision. By tilting the charge coupled device (CCD) plane of portable 3D scanning system according to the Scheimpflug condition, the depth-of-view is successfully extended from less than 40 to 100 mm. Based on the tilted camera model, the traditional two-step camera calibration method is modified by introducing the angle factor. Meanwhile, a novel segmental calibration approach, i.e., dividing the whole work range into two parts and calibrating, respectively, with corresponding system parameters, is proposed to effectively improve the measurement accuracy of the large depth-of-view 3D laser scanner. In the process of 3D reconstruction, different calibration parameters are used to transform the 2D coordinates into 3D coordinates according to the different positions of the image in the CCD plane, and the measurement accuracy of is obtained experimentally. Finally, the experiment of scanning a lamina by the large depth-of-view portable 3D laser scanner used by an industrial robot IRB 4400 is also employed to demonstrate the effectiveness and high measurement accuracy of our scanning system.