双目视觉测量系统的标定及3维测量

针对结构光形位公差视觉测量系统,提出了一阶径向畸变的摄像机成像模型和标定方法,并对传统的直接线性变换(DLT变换)标定算法做了些改进。即先针对没有畸变的线性模型,利用传统的标定算法,解线性超定方程组求解摄像机的全部参数,再针对引入一阶径向畸变的成像模型,以线性模型的参数为初值,通过非线性迭代优化摄像机的图像中心,等效焦距,倾斜因子,畸变系数等内部参数。实验结果表明,该方法无需预标定,精度适中,是相对简单实用的标定方法。     

一种新的摄像机线性标定方法

计算机视觉中,在对景物进行定量分析或对物体进行精确定位时,都需要进行摄像机标定,即准确确定摄影机的内部参数和外部参数,因此寻找新的快速有效的摄像机标定计算方法是计算机视觉应用中的一个重要问题。为也快速有效地进行摄像机的标定,并针对常用的带有一阶径向畸变的摄像机模型,提出了一种线性求解摄像机参数的标定方法,它可分步标定各参数,且全部采用线性方法求解,从而避免了非线性优化中的不稳定性,使得算法更为实用,简单快捷。实验结果表明,该方法具有较高的标定精度,是一种实用的标定方法。     

基于一阶径向畸变算法的双目摄像机多位姿标定方法

双目立体视觉中在对物体进行三维测量或精准定位时,需要对摄像机进行标定以获得其内外参数。研究径向畸变摄像机模型,构造了基于一阶径向畸变（RAC）算法的双目摄像机内外参数线性求解公式。考虑侧倾角、旋转角、俯仰角以及透镜的主要畸变因素,修正了传统RAC标定法中只考虑径向畸变、部分参数需要先验值的缺陷。利用标定所得内、外参数进行了多位姿双目摄像机三维重构实验。实验结果表明,该标定方法重投影误差分布在[-0.3,0.3],动态识别结果与实际运行轨迹重合率为96%,对降低双目立体视觉三维测量误差率有积极性影响。     

Tsai氏相机平面标定算法的一种解析改进

针对径向畸变的针孔透视投影模型,提出了一种简单快速的相机标定算法。该算法在假设图像中心点与CCD或CMOS传感器中心重合的前提下,将相机的内外参数和相机模型的畸变参数分离,以进一步进行线性相机标定,避免了非线性优化带来的误差,降低了算法复杂度,可适当提高标定精度,节约计算时间。首先,根据透视投影的交比不变性原理标定镜头的畸变系数;然后,根据旋转变换关系和平移变换关系,充分利用径向畸变约束、旋转变换的正交性和旋转矩阵特有的性质约束线性求解出相机的内参和外参;最后,通过实验与Tsai氏相机平面标定算法进行对比,所提算法在标定时间上节约了35%左右,在精度上至少提高了15%。     

基于畸变校正的双目立体摄像机线性标定

利用透视变换原理建立双目立体摄像机数学模型,全面考虑了镜头的径向畸变和切向畸 变,提出一种线性求解摄像机参数的标定方法,改变了以往的摄像机标定依赖于非线性优化的缺点,避免了非线性优化的不稳定性.该标定方法在单摄像机模型的基础上,加入对双摄像机相对位置的确定,通过成像过程中坐标系之间的转换,较好地实现了双目立体摄像测量系...     

基于直线的几何不变性标定摄像机参数

计算机视觉通常采用针孔摄像机模型,但对于存在较大畸变的鱼眼镜头或广角镜头来说,会造成图像中同时存在透视变形和像差畸变。解决此问题的传统方法一般是采用标准网格板来标定摄像机参数,但需要较多的已知信息。为了进行精确的标定,提出了一种新的标定方法,该新方法不需要任何空间3维信息,即可用单幅普通图像来标定摄像机的像差系数及内参数,并可将畸变图像校正到相似变换。为了纠正像差畸变和计算消影点,该方法采用了直线的射影不变性,即共线点的投影仍然共线,平行直线束的投影相交于一点的性质;为了纠正透视变形,还采用了直线的相似不变性,即正交直线的夹角在相似变换中仍然保持正交的性质。用该方法标定的摄像机的参数包括像差系数、焦距、主点和纵横比,同时将图像纠正到了相似变换。用实验室图像和室外图像进行了仿真实验都得到了精确、可靠的结果。     

一种摄像机成像误差的模型化修正方法

本文针对摄像机成像误差问题,首先提出了一种新 的径向畸变模型,利用此模型推出了能精确标定摄像机的关键参数（有效焦距、平移矢量的 Z向分量以及径向畸变系数）的线性算法;同时提出了一种成像系统误差的修正模型,并利 用系统辨识方法正确估计了该模型的各参数;并进行了实验验证.这项研究必将使得摄像机 成像的误差整体降低,从而提高了测量精度.     

快速有效的摄像机标定方法

提出了一种快速有效的基于径向约束的两步算法.该算法综合了线性模型和非线性模型的优点,在求解摄像机参数的过程中,采用线性模型标定摄像机中的一部分参数,进一步考虑非线性畸变,通过条件化简将非线性方程转化成线性方程求解其余摄像机参数,有效避免了直接求解非线性方程带来的计算繁琐和结果不稳定的缺陷.最后对标定结果采取最优化算法求精.实验结果表明,优化后的两步算法提高了摄像机标定的效率和准确性.     

一种摄像机亚象素线性标定方法

提出了一种考虑径向畸变的摄像机线性标定方法。采用一个方格图样模板进行标定,先利用改进的Harris算子精确提取角点的亚象素坐标,通过预标定获得主点坐标;然后在考虑摄像机径向畸变的情况下建立摄像机模型,并求解摄像机内外参数。实验及误差分析表明:该标定方法具有较高的精度和较好的实时性。     

一种考虑二阶径向畸变的主动视觉自标定算法

基于主动视觉的摄像机自标定是摄像机标定的一个重要分支 ,由于普通的 CCD摄像机拍摄的像片存在着各种类型的几何畸变 ,其中以径向畸变最为严重 ,因此研究考虑径向畸变的自标定技术有着重要的意义 .为了使标定结果更精确 ,提出了一种考虑二阶径向畸变的内参数自标定方法 ,并通过推导考虑二阶径向畸变的极线几何约束 ,得出了如果能控制摄像机做 4次不在同一平面上的平移运动 ,则可以标定摄像机的内参数和二阶径向畸变系数的结论 .仿真实验结果表明 ,该算法精度很高 ,且具有一定的鲁棒性 ,可用于摄像机的标定 .     

Camera calibration with distortion models and accuracy evaluation

A camera model that accounts for major sources of camera distortion, namely, radial, decentering, and thin prism distortions is presented. The proposed calibration procedure consists of two steps: (1) the calibration parameters are estimated using a closed-form solution based on a distribution-free camera model; and (2) the parameters estimated in the first step are improved iteratively through a nonlinear optimization, taking into account camera distortions. According to minimum variance estimation, the objective function to be minimized is the mean-square discrepancy between the observed image points and their inferred image projections computed with the estimated calibration parameters. The authors introduce a type of measure that can be used to directly evaluate the performance of calibration and compare calibrations among different systems. The validity and performance of the calibration procedure are tested with both synthetic data and real images taken by tele- and wide-angle lenses     

Self-calibration of hybrid central catadioptric and perspective cameras

Hybrid central catadioptric and perspective cameras are desired in practice, because the hybrid camera system can capture large field of view as well as high-resolution images. However, the calibration of the system is challenging due to heavy distortions in catadioptric cameras. In addition, previous calibration methods are only suitable for the camera system consisting of perspective cameras and catadioptric cameras with only parabolic mirrors, in which priors about the intrinsic parameters of perspective cameras are required. In this work, we provide a new approach to handle the problems. We show that if the hybrid camera system consists of at least two central catadioptric and one perspective cameras, both the intrinsic and extrinsic parameters of the system can be calibrated linearly without priors about intrinsic parameters of the perspective cameras, and the supported central catadioptric cameras of our method can be more generic. In this work, an approximated polynomial model is derived and used for rectification of catadioptric image. Firstly, with the epipolar geometry between the perspective and rectified catadioptric images, the distortion parameters of the polynomial model can be estimated linearly. Then a new method is proposed to estimate the intrinsic parameters of a central catadioptric camera with the parameters in the polynomial model, and hence the catadioptric cameras can be calibrated. Finally, a linear self-calibration method for the hybrid system is given with the calibrated catadioptric cameras. The main advantage of our method is that it cannot only calibrate both the intrinsic and extrinsic parameters of the hybrid camera system, but also simplify a traditional nonlinear self-calibration of perspective cameras to a linear process. Experiments show that our proposed method is robust and reliable.     

基于改进的SUSAN法的摄像机线性标定方法

设计并实现了一种考虑径向畸变的逐步线性摄像机标定方法。结合边缘检测，缩小了SUSAN法检测角点的范围，并利用角点的邻域特征，剔除伪角点，从而提高了SUSAN法角点检测的速度和准确度。利用此改进的SUSAN法精确提取方格模板角点的亚像素坐标，并通过预标定获得主点坐标；然后在考虑摄像机径向畸变的情况下建立摄像机模型，并求解摄像机内外参数。最后通过实验及误差分析表明，本标定方法具有较高的精度和较好的实时性。     

由灭点进行径向畸变的自动校正

目的镜头畸变影响着3维重建、几何量测等工作的质量。根据图像中的灭点几何约束条件,提出一种根据灭点进行弱径向畸变自动校正方法。方法为避免包含畸变中心参数的非线性模型优化结果的不稳定性,在求解径向畸变系数之后进一步对畸变中心进行优化。首先根据灭点几何约束条件建立关于灭点与径向畸变系数的非线性模型,使用Levenberg-Marquardt(LM)算法估计灭点坐标与径向畸变参数,然后根据质量评价准则对畸变中心和径向畸变系数进一步迭代优化;最后,通过真实图像对该方法的可行性进行分析验证。结果采用不同的数据对径向畸变进行了有效地校正,并采用校正后的数据进行了相机标定,标定结果相对于传统基于非量测校正方法有明显的提高。结论充分利用图像中的灭点属性,提出一种新的镜头径向畸变校正方法。实验结果表明,该方法能够有效地对径向畸变进行校正,并克服了传统基于非量测畸变校正方法的不稳定性。     

一种基于斜率的摄像机畸变校正方法

普通 CCD摄像机在成像时都存在畸变成像误差 ,在机器人视觉检测及自动装配中 ,有效地进行误差校正对准确确定物体的位置具有重要的意义 .本文采用带有一阶径向畸变的小孔摄像机模型 ,提出一种基于线段斜率的方法 ,对摄像机镜头的径向畸变进行校正 ,不必标定太多的摄像机的外参数 ,方法简洁 ,适合于视觉系统中对摄像机畸变的实时校正 ,或对摄像机捕获的图像进行几何校正 .实验表明 ,具有很强的鲁棒性和较高的校正精度     

A new calibration model of camera lens distortion

Lens distortion is one of the main factors affecting camera calibration. In this paper, a new model of camera lens distortion is presented, according to which lens distortion is governed by the coefficients of radial distortion and a transform from ideal image plane to real sensor array plane. The transform is determined by two angular parameters describing the pose of the real sensor array plane with respect to the ideal image plane and two linear parameters locating the real sensor array with respect to the optical axis. Experiments show that the new model has about the same correcting effect upon lens distortion as the conventional model including all the radial distortion, decentering distortion and prism distortion. Compared with the conventional model, the new model has fewer parameters to be calibrated and more explicit physical meaning.     

Hand–eye calibration with epipolar constraints: Application to endoscopy

In this paper, we propose a new calibration method for a hand–eye system equipped with a camera undergoing radial distortion as a rigid endoscope. While classic methods propose either a separated estimation of the camera intrinsics and the hand–eye transform or a mixed non-linear estimation of both hand–eye and camera intrinsics assuming a pin-hole model, the proposed approach enables a simultaneous refinement of the hand–eye and the camera parameters including the distortion factor with only three frames of the calibrated pattern. We propose and compare two criteria to minimize: (i) the first one is based on the epipolar constraint between pairs of frames and (ii) the second one expresses the camera extrinsic with respect to hand–eye and world-grid transforms in the single frame reprojection error. We run bundle-adjustment on each criterion with respect to the distortion parameters, the camera intrinsics and the hand–eye transform. Our method allows us to recover more accurate 3D shapes when compared to state-of-the-art non-linear methods.