一种立体视觉测量高精度标定新方法

提出一种实现通用摄像机标定和现场高精度立体视觉传感器标定的新方法。该方法无需预先给定初始参数,而是根据投影矩阵计算摄像机参数的初始值,结合镜头畸变的标定数学模型,实现通用摄像机标定;在立体视觉传感器三维测量模型基础上,引入目标距离约束建立结构参数标定优化目标函数,从而得到使空间距离偏差最小的最优结构参数,实现传感器现场高精度标定。实验结果表明,上述方法标定精度较高,已标定传感器空间距离测量相对误差小于0.45%。     

关节式坐标测量机激光测量头参数标定

在三维视觉测量中,标定方法对测量结果的影响是决定性的.本文通过分析、比较各种视觉模型及标定方法,采用考虑镜头畸变因素的三维视觉模型以满足高精度测量系统的需求.由于关节式坐标测量机的激光测量头,使用单摄像机和线结构光来匹配被测物体表面的三维数据,本文设计了一种新型的阶梯形标定块,通过标定块图像和激光条纹图像完成了摄像机的内外参数标定和激光平面参数标定.实验证明,该标定操作过程简单,易于实现自动化,且具有较高的标定精度.     

一种面结构光投影仪的标定方法

目的 研究并提出一种简单的面结构光投影仪的标定方法,结合试验搭建的测量平台,实现对饮料瓶、易拉罐、瓶盖等形状规则的包装件以及轮廓复杂人脸的准确测量。方法 首先借助二维灰度棋盘格标定板并采用张正友法标定好摄像机,再向标定板投影设定好的黑白棋盘格图案,然后结合图像阈值分割和形态学操作方法获取相机捕获投影图案的特征点坐标,最后使用标定好的摄像机参数来标定投影仪。结果 文中提出的标定方式相对操作简单、成本低,且在x和y方向的重投影误差基本都小于1个像素。结论 测量实验结果表明,文中标定方法能保证对人脸模型较理想的测量精度,有较好的应用范围。     

基于同视场参考点的落点坐标测量系统的设计与应用

提出了一种用于测量空间三维点坐标的单摄像机模型。该模型利用透视投影几何关系,对摄像机参数进行标定,制定固定关联基准,建立参考点与被测点的平面方程,利用这两个条件,建立相应的数学模型,通过读取单目CCD摄像机像面坐标,就可重建物体落点的三维坐标。     

摄像机标定中光心图像坐标确定方法

在分析传统的摄像机光心确定方法的优缺点的基础上,提出了一种改进的径向准直约束法和一种带约束条件的投影矩阵分解法。将由两种改进的方法和直接光学法得到的光心坐标和直接用图像中心坐标近似代替的光心坐标一同进行摄像机的标定与测量研究。实验与仿真结果证明,由所提出的两种方法求得的光心图像坐标在进行标定与三维测量时可达到较高的精度并且优于直接用图像中心坐标进行标定与三维测量的精度。     

图像测速法的摄像机标定技术

针对漂浮在空气中或者液体中的粒子的速度测量,提出了一种基于双目视觉的测量方法。采用两个光轴相互垂直的CCD摄像机,分布在测量腔体的左右两侧。结合系统的几何结构特点,两个CCD摄像机分别标定,将标定模型方程转化为多项式形式,利用最小二乘原则获取平面模型标定参数,然后再利用公垂线距离最短原则实现三维坐标测量。实验给出了三维坐标的偏差分布图,证明这是一种实用有效快速的标定方法。     

双目立体视觉中特征点三维坐标重构校准研究

双目立体视觉是一种商业化较成熟的三维测量技术,左右摄像机内外参数的精确标定是实现三维重构的基础和关键。针对棋盘格和圆点两种标定板图案研究了相应的图像处理技术,实现了标定点的亚像素精度定位及其有效排序。采用基于单映性约束和非线性优化的多视角平面标定算法实现了摄像机光学及空间位置参数求解。用极线约束残差法衡量标定结果的准确度。基于桥式三坐标标准实现标定点三维重构平面度以及多平面空间夹角测量结果的校准,基于光学三坐标标准实现了标定点三维重构空间距离的校准,并分析了校准结果的不确定度。圆标志点三维重构空间距离示值误差为0.029 mm,不确定度U=24 μm（k=2）     

3D测量系统中的高精度摄像机标定算法

本文在分析完整的摄像机镜头畸变模型的基础上,提出了一种新的标定算法.该算法包括三个步骤,首先在不考虑镜头畸变的情况下利用标定块上的中间若干个点,采用线性优化方法求出除畸变系数以外的其他外部参数和主要的内部参数;然后固定上述已求得的参数,利用线性优化方法求解畸变系数;最后对所有内部参数和外部参数进行全局非线性优化.最后对本文的标定算法进行了标定实验,实验结果表明,本文算法的标定精度可以达到0.0367 mm,可以满足高精度三维测量及其他应用的要求.     

仿生复眼系统标定及测量方法研究

为了实现对近景目标物的三维测量,研制了一种小型仿生复眼系统。介绍了该复眼系统的结构及其参数设计原则,并对该系统采用的标定、三维测量等算法进行研究。首先根据复眼成像特点搭建了标定和测量平台,并分别使用张正友的方法、直接线性变换法、Tsai式两步法三种摄像机标定方法对复眼的中心子眼进行标定,通过比较实验结果发现Tsai式标定方法精度更高,更适用于本复眼系统的标定。然后针对边缘子眼光轴与图像传感器不垂直问题,提出了一种新的图像畸变数学模型,有效的提高了边缘子眼的标定精度。最后建立了多子眼三维探测模型,并探索了多子眼成像对复眼相机测量精度的影响,认为三子眼可获得比双子眼更高的精度和稳定性。实验结果表明,在距离复眼相机150?260 mm范围内,该复眼探测系统的三维测量相对误差在2%左右,在满足仪器小型化的同时能基本实现近景三维测量。     

船用光电系统中摄像机参数的标定方法

基于一阶径向畸变的针孔摄像机模型,提出了一种新的线性三步摄像机定标方法,即通过径向排列约束计算摄像机参数的旋转矩阵、X轴平移矢量和Y轴平移矢量;根据透视投影的交比不变性解算一阶径向畸变参数;利用求得的摄像机参数建立有效焦距和Z轴平移矢量的线性方程,采用最小二乘法得到线性解。实验表明,该方法简单快捷,具有较高的标定精度,解决了原有算法采用非线性搜索寻优可能存在的解不稳定性等问题。     

Flexible three-dimensional measurement technique based on a digital light processing projector

A new method of 3D measurement based on a digital light processing (DLP) projector is presented. The projection model of the DLP projector is analyzed, and the relationship between the fringe patterns of the DLP and the fringe strips projected into the 3D space is proposed. Then the 3D shape of the object can be obtained by this relationship. Meanwhile a calibration method for this model is presented. Using this calibration method, parameters of the model can be obtained by a calibration plate, and there is no requirement for the plate to move precisely. This new 3D shape measurement method does not require any restrictions as that in the classical methods. The camera and projector can be put in an arbitrary position, and it is unnecessary to arrange the system layout in parallel, vertical, or other stringent geometry conditions. The experiments show that this method is flexible and is easy to carry out. The system calibration can be finished quickly, and the system is applicable to many shape measurement tasks.     

Three dimension reconstruction through measure-based image selection

Three dimension (3D) reconstruction is one of the research focus of computer vision and widely applied in various fields. The main steps of 3D reconstruction include image acquisition, feature point extraction and matching, camera calibration and production of dense 3D scene models. Generally, not all the input images are useful for camera calibration because some images contain similar and redundant visual information. These images can even reduce the calibration accuracy. In this paper, we propose an effective image selection method to improve the accuracy of camera calibration. Then a new 3D reconstruction algorithm is proposed by adding the image selection step to 3D reconstruction. The image selection method uses structure-from-motion algorithm to estimate the position and attitude of each camera, first. Then the contributed value to 3D reconstruction of each image is calculated. Finally, images are selected according to the contributed value of each image and their effects on the contributed values of other images. Experimental results show that our image selection algorithm can improve the accuracy of camera calibration and the 3D reconstruction algorithm proposed in this paper can get better dense 3D models than the normal algorithm without image selection.     

Toward dynamic recalibration and three-dimensional reconstruction in a structured light system

We present a method for dynamic recalibration and 3D reconstruction via a structured light system. Assuming that the light planes cast from the digital light projector have been calibrated off-line, we show that the focal length, aspect ratio, and all motion parameters of the camera can be determined on-line. Then the 3D reconstruction can be carried out by either a traditional triangulation method or a more efficient transformation-based method. In the latter method, a single image is sufficient for the whole process of calibration and reconstruction. Thus a hand-held camera can be used. Computer simulation and real data experiments were carried out to validate the method.     

AHSPP Annual Conference

Abstract

A calibration and three-dimensional (3D) reconstruction method is presented based on images reflected from planar mirrors and acquired with one camera. The geometric model of the camera–mirror set and a method of calibrating it are described. The calibration technique computes the model parameters using linear equations, and it is proved that the calibration is possible with the knowledge of only six 3D points. The reconstruction method is based on a volumetric representation. The 3D reconstruction is based on a space carving algorithm and the calibration method described in the paper. The results of the calibration and reconstruction method show the efficiency of both techniques. This set-up enables a simple and inexpensive multi-ocular system to be built to recover the 3D structure of volumes.     

Accurate phase–height mapping algorithm for PMP

In phase measurement profilometry (PMP), the projector can be regarded as another camera according to the reversibility of the light path principle. The relationship of projecting spatial points to image plane of camera and projector is studied, and the phase–height mapping equation without projector distortion is obtained. The equation is then expanded to a polynomial for the convenience of calibration. Furthermore, the relation between the distortion value and the phase is investigated. Finally the phase–height mapping algorithm considering projector distortion and its polynomial expression are acquired. The accuracy of approximation is studied and compared with another two existing algorithms by computer simulation. It is revealed that the absolute error of the new algorithm expressed with quartic polynomial reaches 5.380× 10^?3 mm and its standard deviation reaches 3.354× 10^?4 mm under general lens distortion. The accuracy of the new algorithm is the highest among the three algorithms. In experiment, the standard deviation of the measurement reaches 0.04 mm even though the result is affected by measurement error.     

Stereo calibration of binocular ultra-wide angle long-wave infrared camera based on an equivalent small field of view camera

ABSTRACT

In this paper, a stereo calibration method for binocular ultra-wide angle long-wave infrared camera is proposed on the basis of an equivalent small field of view camera. Extrinsic parameters are calibrated through the corrected images from the left and right cameras. They can be viewed as images taken by a small field of view camera. The calibration procedure consists of three steps: monocular calibration, distortion correction and extrinsic parameters calibration. In order to evaluate the accuracy of the method, stereo vision of the camera is modelled and a 3D reconstruction approach is presented. A series of experiments, including intrinsic parameters, extrinsic parameters and 3D reconstruction, are conducted to validate the proposed method. The results show that the baseline length error decreases to 0.67%, and the relative error for the 3D reconstruction of corners is smaller than 8.11%. In contrast to the common stereo calibration method, it improves calibration accuracy.     

Three-dimensional shape measurement and calibration for fringe projection by considering unequal height of the projector and the camera

In fringe projection, the CCD camera and the projector are often placed at equal height. In this paper, we will study the calibration of an unequal arrangement of the CCD camera and the projector. The principle of fringe projection with two-dimensional digital image correlation to acquire the profile of object surface is described in detail. By formula derivation and experiment, the linear relationship between the out-of-plane calibration coefficient and the y coordinate is clearly found. To acquire the three-dimensional (3D) information of an object correctly, this paper presents an effective calibration method with linear least-squares fitting, which is very simple in principle and calibration. Experiments are implemented to validate the availability and reliability of the calibration method.     

彩色伪随机编码闪光投影系统的建模及其标定

为实现仅用一幅图象在真正的三维欧氏空间重构三维场景,尤其是动态的三维场景,系统需要对彩色伪随机编码闪光投影系统进行建模和预标定。当系统参数改变后,利用伪随机编码图案的几何约束,不需重新标定,可实现自适应重构三维场景。通过对投影仪像质的的无畸变性分析,用线性模型对投影仪成像过程进行建模,并提出一种高精度的投影系统直接标定方法,通过测出靶标上各投影编码特征点在空间的三维齐次坐标,求出内外参数实现了对投影仪的预标定。标定精度达到0.1单元格,欧氏重构结果较为理想。     

基于PSO和LSSVM回归的摄像机标定

针对摄像机非线性显式标定时很难精确地建立其复杂的数学模型,本文提出了基于粒子群优化算法(PSO)和最小二乘支持向量机(LSSVM)回归的摄像机非线性隐式标定方法.该方法采用最小二乘回归机精确逼近图像坐标与世界坐标之间复杂的非线性成像关系;利用PSO算法搜索LSSVM回归模型的最优参数,提高LSSVM回归的收敛速度和泛化能力.通过运用标准BP神经网络、遗传算法、LSSVM及粒子群优化的LSSVM回归方法对圆阵列图案标定模板进行标定,实验结果表明:基于PSO和LSSVM回归的标定方法具有标定精度高、收敛速度快、泛化能力强等优点.