基于立体视觉的水下三维测量系统研究

随着我国海洋战略的提出,对于海洋观测技术和装备的需求日趋迫切。针对现有水下成像系统无法实现精确三维测量这一难题,该文提出了一种基于双目立体视觉原理的水下三维测量系统研究方法,并对其可行性进行了验证。针对水下成像过程存在的水体界面折射问题,该文提出了相应的相机成像模型及系统参数标定方法,建立了防水深度达 30 m 的双目水下测量及照明装置,并在水池、近海条件下进行了实地测试。实验结果显示,在水体条件较好的情况下,系统观测距离可达 8 m 以上,有效测量距离为 0.5～4.5 m,在 0.5 m 和 4.5 m 距离处的测量误差分别为 2 mm 和 20 mm。实验验证了 水下双目成像模型、立体标定、测量模型等方法的有效性和精确性,可为水下检修作业等海洋工程行业提供一种有效的三维测量技术手段。     

基于双目立体视觉技术的桥梁裂缝测量系统

针对国内外桥梁裂缝测量效率低、成本高、精度低等现状,提出了一种基于双目立体视觉技术的桥梁裂缝测量系统。采用相机标定、图像匹配、三维坐标计算等双目立体视觉技术对桥梁裂缝的宽度和长度进行计算,实现了桥梁裂缝测量系统。实验通过与单目摄像机用图像处理方法计算的桥梁尺寸结果作对比,表明:对于同一条裂缝的宽度与长度,用所提方法在不同拍摄角度下计算结果差别不大,并且与真实值的相对误差分别保持在10%和1%以内,而同一条件下单目测量系统的计算结果则随着拍摄角度的变化相差很大,宽度测量误差最大达到了19.41%,长度测量误差最大达到了54.35%。说明基于双目立体视觉技术的桥梁裂缝测量系统可以应用于实际中,并且鲁棒性更强,测量结果更精确。     

FPGA based disparity map computation with vergence control

Depth estimation in a scene using image pairs acquired by a stereo camera setup, is one of the important tasks of stereo vision systems. The disparity between the stereo images allows for 3D information acquisition which is indispensable in many machine vision applications. Practical stereo vision systems involve wide ranges of disparity levels. Considering that disparity map extraction of an image is a computationally demanding task, practical real-time FPGA based algorithms require increased device utilization resource usage, depending on the disparity levels operational range, which leads to significant power consumption. In this paper a new hardware-efficient real-time disparity map computation module is developed. The module constantly estimates the precisely required range of disparity levels upon a given stereo image set, maintaining this range as low as possible by verging the stereo setup cameras axes. This enables a parallel-pipelined design, for the overall module, realized on a single FPGA device of the Altera Stratix IV family. Accurate disparity maps are computed at a rate of more than 320 frames per second, for a stereo image pair of 640 × 480 pixels spatial resolution with a disparity range of 80 pixels. The presented technique provides very good processing speed at the expense of accuracy, with very good scalability in terms of disparity levels. The proposed method enables a suitable module delivering high performance in real-time stereo vision applications, where space and power are significant concerns.     

双目视觉测量系统摄像机外部参数标定研究

针对双目立体视觉测量系统中摄像机标定问题,讨论了基于标准长度的外部参数标定方法,选定了摄像机透视投影模型,采用双摄像机同时对放置于视场内的十字靶标拍摄多幅图像,得出了基于LabVIEW开发的摄像机标定方法.该方法利用了LabVIEW的开发环境,使用了数学工具包,将遗传算法与LM算法相结合,优化迭代获得摄像机外部参数,运算速度和精度大大提高.开发的模块可用于基于LabVIEW开发的工程软件进行高精度尺寸现场测量.在双目立体视觉测量系统标定结果基础上对标准靶进行测量,测量结果标准差达到0.1.     

A Mobile Robotic Measurement System for Large-scale Complex Components Based on Optical Scanning and Visual Tracking

Large-scale components with complex curved surfaces are the foundation of aerospace, energy, and transportation fields, while full-field 3D measurements along with accuracy analyses are critical to control manufacturing quality. Most of the existing measurement methodologies rely on manual inspection, and the accuracy and efficiency are unsatisfactory. This paper introduces an integrated mobile robotic measurement system for the accurate and automatic 3D measurement of large-scale components with complex curved surfaces. The measurement system is composed of a mobile manipulator, a fringe projection scanner and a stereo vision system, and it can provide accurate noncontact 3D measurements of large-scale complex components. By proposing a hand-eye calibration method and scanning pose tracking method based on a stereo vision system, the local point clouds obtained by scanning along with the movement of the mobile robot around the component can be accurately unified into a common reference frame. The proposed measuring system and method are verified by measuring and reconstructing the whole surface of a wind turbine blade model with a length of 2.8 m. The accuracy evaluation proves the effectiveness of the proposed system and method.     

Analysis of Tsai calibration method using two- and three-dimensional calibration objects

Camera calibration is a fundamental process for both photogrammetric and computer vision. Since the arrival of the direct linear transformation method and its later revisions, new methods have been developed by several authors, such as: Tsai, Heikkilä and Zhang. Most of these have been based on the pinhole model, including distortion correction. Some of these methods, such as Tsai method, allow the use of two different techniques for determining calibration parameters: a non-coplanar calibration technique using three-dimensional (3D) calibration objects, and a coplanar technique that uses two-dimensional (2D) calibration objects. The calibration performed by observing a 3D calibration object has good accuracy, and produces very efficient results; however, the calibration object must be accurate enough and requires an elaborate configuration. In contrast, the use of 2D calibration objects yields less accurate results, is much more flexible, and does not require complex calibration objects that are costly to produce. This article compares these two different calibration procedures from the perspective of stereo measurement. Particular attention was focused on the accuracy of the calculated camera parameters, the reconstruction error in the computer image coordinates and in the world coordinate system and advanced image-processing techniques for subpixel detection during the comparison. The purpose of this work is to establish a basis and selection criteria for choosing one of these techniques for camera calibration, according to the accuracy required in each of the many applications using photogrammetric vision: robot calibration methods, trajectory generation algorithms, articulated measuring arm calibration, and photogrammetric systems.     

结构光测量系统的投影仪标定方法研究

传统单目视觉结构光测量系统通过解相位间接计算被测物的高度信息,系统约束性过强、不易操作、且标定精度较低.将双目立体视觉原理引入单目结构光视觉测量系统,根据投影仪图像坐标和摄像机图像坐标的对应关系,将投影仪当作一个逆向的相机,建立了投影仪模型,使用成熟的相机标定算法对投影仪进行标定.再配合四步相移法和基于多频外差原理的时域相位展开法,实现条纹图像的快速精确解相位.相对于传统的单目视觉结构光测量系统,本方法具有单目视觉系统操作简单、鲁棒性强的特点,同时也可以达到双目视觉测量的精度.实验结果表明,这种方法的投影仪标定精度达到了实际应用的要求.     

Multi-object detection and tracking by stereo vision

This paper presents a new stereo vision-based model for multi-object detection and tracking in surveillance systems. Unlike most existing monocular camera-based systems, a stereo vision system is constructed in our model to overcome the problems of illumination variation, shadow interference, and object occlusion. In each frame, a sparse set of feature points are identified in the camera coordinate system, and then projected to the 2D ground plane. A kernel-based clustering algorithm is proposed to group the projected points according to their height values and locations on the plane. By producing clusters, the number, position, and orientation of objects in the surveillance scene can be determined for online multi-object detection and tracking. Experiments on both indoor and outdoor applications with complex scenes show the advantages of the proposed system.     

A Time-Delay Control Approach for a Stereo Vision Based Human-Machine Interaction System

In this paper, an approach to control a 6-DoF stereo camera for the purpose of actively tracking the face of a human observer in the context of Human-Robot Interaction (HRI) is proposed. The main objective in the presented work is to cope with the critical time-delay introduced by the computer vision algorithms used to acquire the feedback variable within the control system. In the studied HRI architecture, the feedback variable is represented by the 3D position of a human subject. We proposed a predictive control method which is able to handle the high time-delay inserted by the vision elements into the control system of the stereo camera. Also, along with the predictive control approach, a novel 3D nose detection algorithm is suggested for the computation of the feedback variable. The performance of the implemented platform is given through experimental results.     

一种基于弹道曲线模型的脱靶量测试方法

针对传统的脱靶量测试设备体积庞大、不便移动且测试成本高等缺点,提出了一种基于弹道曲线模型的双目立体视觉的脱靶量测试方法。研究了摄像机的成像模型及坐标系变换,分析了摄像机标定的一般方法,构建了摄像机标定模型,并推导了标定参数的表达式。基于双目立体视觉测试技术设计了弹道曲线模型的弹丸脱靶量测量系统,其测量过程简单且标定结果稳定,可实现弹丸运动目标的快速检测,通过对运动目标的空间定位和轨迹拟合实现了脱靶量的测试。实验结果表明:弹道直线模型和曲线模型均能简便地求解飞行弹丸脱靶量,后者比前者更贴近实际弹丸飞行轨迹,可获得更高精度的脱靶量,弹道曲线模型的脱靶量平均绝对误差(MAE)比直线模型降低了大约一半。     

基于双目内窥镜的散斑三维重建系统研究

传统的内窥镜只能提供清晰的图像,无法进行三维测量和三维重建.该文提出一种基于立体视觉原理的双目内窥镜系统,用于实现三维测量和三维重建,并开发了一套基于双目内窥镜的散斑三维重建系统.为了提高系统的标定精度和三维重建质量,该文提出一种高精度双目内窥镜标定参数优化方法及基于光轴双次旋转的立体校正算法.其中,测量系统由一个结构...     

双目立体视觉系统的非线性模型建立

构建实用的立体视觉系统及选用适合的系统模型是立体视觉研究的基础和重要内容。对双目立体视觉系统的结构形式进行分析和比较,采用相交光轴的结构形式构建立体视觉实验系统;推导双CCD摄像机系统的数学模型,在系统模型中考虑非线性径向畸变因素的影响,该数学模型可直接用于立体视觉系统的摄像机标定。     

Fast Relative Depth Computation for an Active Stereo Vision System

Real-time computation of exact depth is not feasible in an active vision setup. Instead, reliable relative depth information which can be rapidly computed is preferred. In this paper, a stereo cue for computing relative depth obtained from an active stereo vision system is proposed. The proposed stereo cue can be computed purely from the coordinates of points in the stereo pair. The computational cost required is very low. No camera calibration or prior knowledge of the parameters of the stereo vision system is required. We show that the relationship between the relative depth cue and the actual depth in the three-dimensional (3D) space is monotonic. Such a relation is maintained even when the focal length and the vergence angle are changed, so long as the focal lengths of the two cameras are similar. Therefore, real-time implementation in an active vision setup can be realized. Stability analysis shows that the proposed method will be stable in practical situations, unless the stereo camera diverges. Experimental results are presented to highlight the properties and advantages of the proposed method.     

基于多目立体视觉的试件飞行运动速度测量方法研究

为了测量试件的飞行速度,提出了一种基于多目立体视觉技术的飞行运动速度测量方法。首先研究了多目相机的标定方法,然后通过图像匹配的方法来获取各个相机图像中目标点的图像位置,最后根据各个相机的内部和外部参数,重建得到被测试件的三维坐标,结合相机的拍摄速度,计算出试件的飞行速度。结果表明：该方法可以较为准确的测量出试件在整个飞行过程中的运动速度,且具使用灵活,操作方便等特点。     

五自由度立体视觉平台中摄像机的标定

文章从立体视觉与机器人控制集成的角度出发,建立了一个主动立体视觉跟踪和定位系统,用于柔性装配线中装配零件的运动跟踪和装配工位的精确定位。该系统采用基于平面正方形的摄像机标定方法,该方法要求摄像机在三个(或三个以上)不同的位置摄取一个标准的正方形的图像,经过图像处理找到正方形的四个顶点在图像上的坐标,通过计算就可以线性求解摄像机全部内外参数。该方法简单易懂,非常适合于摄像机内外参数频繁标定的场合,计算速度快、所需设备简单、实用性好。文章的最后,给出了使用文中提出方法进行标定的实验结果,说明了该方法的有效性。     

双目系统全视域采样的SVM标定模型分析

目的 为改善摄像机间接标定采样不全、模型表达模糊问题,实现小视场下检测视域完备采样,提出一种基于双目系统全视域采样的支持向量机（SVM）标定方法。方法 该方法利用六角晶格标定板靶点序号可读特点为基础,采集整个双目系统有效视域中检测点的视差坐标、世界坐标并建立完备的样本集。选取SVM对该样本集进行训练,将SVM算法得到的模型参数代入其决策函数中进行求解,获得公式化的标定模型。由于六角晶格标定板的四角和中心分布了5个互为非中心对称的多边形,可在标定板部分区域被采集的情况下获取标定板位姿信息,进而读取采集的各靶点序号。通过上下移动标定板,利用HALCON算子获取图像中各靶点的序号,建立双目视觉系统检测区域的完备样本集。最后,利用SVM算法训练样本获得标定模型,可以明确表达出标定模型的数学形式。结果 与传统采样建立的模型进行对比分析,实验结果表明该方法建立模型的标定误差减小了24.51%,降低了标定模型在传统方法未采样区域的标定误差,证明了该方法的可行性。结论 提出一种基于双目系统全视域采样的支持向量机标定方法,通过非中心对称的多边形确定标定板上靶点的序号,实现双目视觉系统检测视域的完备采样。实验结果表明该方法提高了摄像机间接标定的精度,具有良好的适用性和鲁棒性,适用于小视域内双目视觉系统的间接标定。     

基于立体视觉的串联机器人跟踪检测系统

建立一种六自由度串联机器人视觉跟踪检测系统框架,包括图像采集、摄像机标定、机器臂跟踪检测、机器臂位姿建模与计算等。提出利用CamShift算法对机器人进行在线粗跟踪,搜寻和画定出机器臂操作器在当前窗口的区域位置。对跟踪到的机器臂按照SURF算法进行特征提取与立体匹配。该方法被用于对串联机器人位姿检测进行实验。实验结果表明,2种算法的结合适用于六自由度串联机器人在空间复杂运动的跟踪检测。     

轮式机器人立体视觉平台的设计与实现

介绍了一种基于轮式机器人的立体视觉平台设计方案.给出了双目立体视觉原理和数学模型,从摄像机定标和对应点匹配两个方面讨论了形状与位置三维重建,阐述了双目立体视觉平台的设计,重点介绍了硬件平台的组成结构及各功能模块的电路组成与功能实现.该系统可根据具体应用情况灵活配置,因而结构合理、实用性强.     

强约束条件下环绕式相机标定方法

目的 在计算机视觉和摄影测量领域,经常应用多视角图像对场景进行高精度的三维重建。其中,相机内参数和相机间固定相对关系的高精度标定是关键环节,文章提出一种能够在强约束条件下快速进行相机标定的方法。方法 通过相机间6个相互独立的约束,充分利用系统的几何条件,确定固有关系,再以共线方程为基础推导强约束条件下的平差模型,并应用于自检校光束法平差,开展相邻立体相机的匹配,实现多相机系统的快速标定。结果 最后通过实验,验证了加了强约束条件后,加大了平差的多余观测数,提高了标定精度和鲁棒性。结论 建立了相机标定系统,提出了在强约束条件下快速进行相机标定的方法,展开了人体三维重建研究,并且该方法可推广到多个相机组成的多相机立体量测系统的标定中。     

双目立体视觉系统的精度分析

为提高双目立体视觉系统的测量精度,分析双目视觉系统的工作原理以及该系统各个环节的误差模型.通过提高标定模板的精度、增加标定图像,可以减小标定误差及图像校正行对齐误差.分析图像识别误差对视觉系统测量精度的影响,导入视觉系统的结构参数与测量误差之间的关系,从而确定结构参数对测量精度的作用.讨论物距对测量精度的影响,并给出合...