共查询到19条相似文献,搜索用时 156 毫秒
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摄像机径向畸变校正和内参估计的单图标定方法 总被引:1,自引:1,他引:0
提出了一种对摄像机的径向畸变进行校正和内参数估计的单图标定方法.拍摄一幅平面标定模板图像,提出若干条直线,拟合在单参数除法畸变模型下的圆弧参数,从而估计出径向畸变.对径向畸变进行校正后,利用标定模板点与经过校正后的图像点之间的对应关系,估计出单应性矩阵.在假定摄像机主点与畸变中心重合的条件下,线性地计算出摄像机焦距初值.以上述线性方法得到的结果为初值,进行非线性优化,最终得到准确的摄像机参数.超广角鱼眼相机和普通数码相机的实验结果表明,本文提出的算法实现简单、适用性广,结果准确,具有较强的实用性. 相似文献
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提出一种利用标准球对显微图像测量系统进行标定的方法.该方法利用显微系统小视场小景深的成像特点简化计算模型,减少标定参数.通过标准球图像在水平和垂直方向上的直径比计算比例因子;利用标准球边缘图像的边缘点集.运用优化的方法来计算成像系统的畸变系数和主点位置.系统的放大倍数由标准球的实际直径来标定得出.利用标准球在多摄像机公共视场内其轮廓在任何位置均可见这一特性,可同时对显微图像测量系统中的多个摄像机进行标定,简化标定过程.实验结果表明,该方法标定精度较高,标定后的测量系统的极限误差3σ为2.4μm. 相似文献
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摄像机标定是机器视觉中的一个重要问题.精确的摄像机标定在涉及定量测量的应用中是非常重要的.摄像机标定的目的是得到摄像机的内部参数和外部参数.通过这些参数我们能够将一个点的三维位置与它的图像平面的坐标相匹配.本文提出了一种基于两步法的摄像机标定方法.第一步,使用基于无畸变的相机模型估计标定参数;第二步,在考虑相机畸变的情况下,对第一步中得到的标定参数通过非线性优化进行迭代优化,并求解畸变系数,包括径向畸变系数和切向畸变系数.用单幅图像即可完成标定,标定过程比两步法更为简洁.实验结果表明,这种算法是简单而有效的. 相似文献
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基于PSO和LSSVM回归的摄像机标定 总被引:1,自引:0,他引:1
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. 相似文献
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光栅投影式三维摄影测量仪的几何标定方法 总被引:1,自引:0,他引:1
光栅投影式三维摄影测量仪利用了时域结构光投影技术和立体视觉测量原理获得三维点坐标。针对传统标定方法易受镜头畸变影响和标定约束方程少导致精度下降的问题,采用了非线性的摄像机和投影机模型,并提出了二维的投影机模型;使用多平面法标定了系统测量所需的摄像机和投影机几何参数;为进一步提高参数精度,采用Levenberg-Marquardt算法优化了摄像机和投影机模型。实验结果表明,该方法操作简单,无需精确的位置和姿态调整,标定的绝对精度为0.2pixel,相对精度为1/5000。 相似文献
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基于摄影资料的图像测距技术已广泛应用于交通事故、考古等不可复原的现场勘察工作中,利用普通相机进行摄影测量也日趋成熟。但是普通相机没有广角镜头相机的取景优势,现场分析也比较局限,因此广角镜头相机逐渐取代普通相机。而广角镜头相机容易产生图像畸变效应。为此,本文基于相机成像原理,通过精确网格模板标定图像,利用相机参数间物理关系计算出相机内参和畸变参数,提出了一种广角镜头相机的快速标定算法,结合拍摄现场图像,精确定位参考模板标志牌在照片中的成像结果,计算出广角镜头相机的外参,建立广角镜头相机摄影测量系统。现场实验应用表明,本算法标定快速、简单、测量精度高,可以应用于交通事故现场勘测。 相似文献
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Camera calibration is a two-step process where first a linear algebraic approximation is followed by a nonlinear minimization. The nonlinear minimization adjusts the pin-hole and lens distortion models to the calibrating data. Since both models are coupled, nonlinear minimization can converge to a local solution easily. Moreover, nonlinear minimization is poorly conditioned since parameters with different effects in the minimization function are calculated simultaneously (some are in pixels, some in world coordinates, and some are lens distortion parameters). A local solution is adapted to parameters, which minimize the function easily, and the remaining parameters are just adapted to this solution. We propose a calibration method where traditional calibration steps are inverted. First, a nonlinear minimization is done, and after, camera parameters are computed in a linear step. Using projective geometry constraints in a nonlinear minimization process, detected point locations in the images are corrected. The pin-hole and lens distortion models are computed separately with corrected point locations. The proposed method avoids the coupling between both models. Also, the condition of nonlinear minimization increases since points coordinates are computed alone. 相似文献
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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. 相似文献
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基于双目立体视觉系统的图像分析以及人工神经网络的三维空间建模算法,设计了一种针对双目立体视觉相机的校准方法,并可应用于运动目标点的轨迹追踪。将均匀分布目标点的校准平面放置在有效视野内的不同位置,通过双目立体视觉系统来捕获处于不同位置的校准平面图像。在图像处理之后,使用校准点中心的二维坐标作为人工神经网络训练的输入样本集,通过建立人工神经网络模型结构,实现目标点二维平面坐标到三维空间坐标的映射关系。采用这种具有通用性的方法,可以有效修正系统中存在的失真因子,获得目标三维位置信息,而无需进行复杂的相机校准操作。实验表明,提出的方案具有良好的可行性和鲁棒性。 相似文献
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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. 相似文献
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Stereo calibration of binocular ultra-wide angle long-wave infrared camera based on an equivalent small field of view camera 总被引:1,自引:0,他引:1
ABSTRACTIn 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. 相似文献