Nonmetric calibration of wide-angle lenses and polycameras

Images taken with wide-angle cameras tend to have severe distortions which pull points towards the optical center. This paper proposes a simple method for recovering the distortion parameters without the use of any calibration objects. Since distortions cause straight lines in the scene to appear as curves in the image, our algorithm seeks to find the distortion parameters that map the image curves to straight lines. The user selects a small set of points along the image curves. Recovery of the distortion parameters is formulated as the minimization of an objective function which is designed to explicitly account for noise in the selected image points. Experimental results are presented for synthetic data as well as real images. We also present the idea of a polycamera which is defined as a tightly packed camera cluster. Possible configurations are proposed to capture very large fields of view. Such camera clusters tend to have a nonsingle viewpoint. We therefore provide analysis of what we call the minimum working distance for such clusters. Finally, we present results for a polycamera consisting of four wide-angle sensors having a minimum working distance of about 4 m. On undistorting the acquired images using our proposed technique, we create real-time high resolution panoramas.     

基于直线约束的非量测数码相机标定

提出一种非量测数码相机标定的直接方法。该方法基于直线约束条件,即在正确进行畸变纠正后,物方空间的三维直线投影到像片平面上也应该是一条直线。为了将畸变直线纠正成理想直线,利用畸变模型对其进行畸变纠正,并采用Levenberg-Marquardt算法对非线性方程组进行求解,解出符合条件的最佳畸变参数。实验结果证明该方法具有较强的鲁棒性与实用性。     

一种基于几何性质的鱼眼图像校正算法

为快速、高效地校正具有径向畸变的鱼眼图像,提出一种基于几何性质的校正算法。根据投影不变性原理以及径向畸变的几何特性,计算畸变直线的斜率,并通过求解线性方程组得出多项式校正模型的参数。实验结果表明,该算法能够以较低的运算复杂度获得较高的校正精度,相比于采用数学迭代拟合直线的方法,该算法在图像整体校正质量上有明显改善。     

基于直线和二次曲线的多回路平面曲线分割

提出了一种多回路平面曲线的分割算法。算法以直线段和二次曲线段作为拟合的基本单元，通过边缘跟踪把多回路的平面曲线分割成曲线段或单回路的封闭曲线，然后在曲线曲率不连续处继续分割。针对一次分割时可能会产生的迷向问题，提出了基于对偶原理的线段合并技术。该算法的结果能简单有效地描述场景中的物体，使高级视觉任务更简单。实验结果表明算法能取得较好的效果。     

Simple calibration algorithm for high-distortion lens camera

A simple and useful calibration method for a TV camera with a high-distortion lens is presented. The parameters to be calibrated are effective focal length, one-pixel width on an image plane, image distortion center, and distortion coefficient. A simple-pattern calibration chart composed of parallel straight lines is introduced as a reference for calibration. An ordinary 2D model fitting is decomposed into two 1D model fittings on the column and row of a frame buffer across the image distortion center by ingeniously utilizing the point symmetry characteristic of image distortion. Some parameters with a calibration chart are eliminated by setting up a calibration chart precisely and by utilizing negligibly low distortion near the image distortion center. Thus, the number of unknown parameters to be calibrated is drastically decreased, enabling simple and useful calibration. The effectiveness of the proposed calibration method is confirmed by experimentation     

基于直线射影特征的摄像机参数标定方法

对于精度要求高、成本低或使用广角镜头的系统,在标定摄像机参数时需要校正镜头畸变.通常在摄像机标定算法中,镜头畸变参数的校正和摄像机参数求解都结合在一起,增加了算法的复杂性,并且依赖标定模板.针对以上问题,提出了一种新的标定方法,即不需要标定模板,也不需要确定空间点的精确坐标.首先通过直线的射影不变性校正镜头畸变参数,再...     

Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper, we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.     

一种基于球面透视投影约束的鱼眼镜头校正方法

鱼眼镜头摄像机具有较大视场，但是，使用鱼眼摄像机拍摄的图像会有非常严重的变形．该文研究基于球面透视投影约束的鱼眼镜头校正方法．球面透视投影约束是指空间直线的球面透视投影为球面上的大圆．作者首先使用含有变形校正参数的鱼眼变形校正模型，将空间直线的鱼眼投影曲线上的点映射为球面点，然后通过球面点到大圆的球面距离最小来拟合大圆，恢复了变形校正参数，从而实现了鱼眼图像的校正．模拟实验和真实图像实验表明，该方法能得到比较满意的校正结果．     

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。     

光学图象几何畸变的快速校正算法

实际光学镜头所成的图象难免会有几何变形，多项式坐标变换法是进行几何修正的有效方法，但是当次数较高的时候，运算量太大，难以应用到实时图象处理系统，为此在分析多项式坐标变换算法的基础上，提出了一次多项式非均匀分片逼近算法。该算法首先将图象非均匀划分成矩形区域，在每个矩形区域内部用一个一次多项式逼近高次多项式。基于对图象畸变的主要因素即径向畸变的分析，该算法的图象划分规则能在保证逼近精度的前提下占用最少的保存模型参数的空间。该算法大大降低了运算量，将运算时间减少了近2／3，同时能很好地保证逼近精度，空间代价也限制在很小的范围内，试验结果表明该算法是图象几何修正的有效方法，具有良好的工程应用价值。     

基于透射变换的印刷品图像归一化研究

印刷品图像归一化在其质量检验中是极其重要的。针对获取的印刷品图像存在一定程度的畸变,提出一种改进的透视变换的归一化方法。为了准确获取图像的直线边缘信息,改进传统Canny检测中阈值自适应能力差的问题,用迭代法获取阈值参数,并加入滤波器有效滤除过于贴近图像边缘的平行直线;针对传统透视变换特征点无法获取问题,首次提出将图像分为三类状态下分别获取图像的特征点信息,求解得出透视变换矩阵对图像进行归一化。实验结果表明,对采集的印刷品图像该算法相对不准率下降了41.2%,可有效解决图像存在的畸变问题。     

一种简单的基于共面的摄像机参数标定方法

共面摄像机标定就是采用平面式模板来确定摄像机内外参数的过程,在此过程中图像像素和二维特征点是已知的。对于共面标定提出了一种简单及有效的方法去标定摄像机参数。即使用帧缓存中的计算机阵列图像直接来标定参数。首先采用预标定的方法标定出图像中心位置,然后根据帧存图像坐标和世界坐标之间的对应关系使用正交矩阵的约束条件来求解,在此算法中假设尺度因子为1,并且不考虑透镜畸变。所提出的算法用数字仿真图像及真实的图像检验。结果显示,所提出的算法具有较好的精度,是一种简单有效的标定方法。     

A Simple Method of Radial Distortion Correction with Centre of Distortion Estimation

This paper presents a new simple method to determine the distortion function of camera systems suffering from radial lens distortion. Neither information about the intrinsic camera parameters nor 3D-point correspondences are required. It is based on single image and uses the constraint, that straight lines in the 3D world project to circular arcs in the image plane, under the single parameter Division Model. Most of former approaches to correct the radial distortion are based on the collinearity of undistorted points. The proposed method in this paper, however, is based on the conclusion that distorted points are concyclic and uses directly the distorted points not undistorted points, therefore it should be more robust. It also computes the centre of radial distortion, which is important in obtaining optimal results. The results of experimental measurements on synthetic and real data are presented and discussed.

Straight lines have to be straight

Most algorithms in 3D computer vision rely on the pinhole camera model because of its simplicity, whereas video optics, especially low-cost wide-angle or fish-eye lenses, generate a lot of non-linear distortion which can be critical. To find the distortion parameters of a camera, we use the following fundamental property: a camera follows the pinhole model if and only if the projection of every line in space onto the camera is a line. Consequently, if we find the transformation on the video image so that every line in space is viewed in the transformed image as a line, then we know how to remove the distortion from the image. The algorithm consists of first doing edge extraction on a possibly distorted video sequence, then doing polygonal approximation with a large tolerance on these edges to extract possible lines from the sequence, and then finding the parameters of our distortion model that best transform these edges to segments. Results are presented on real video images, compared with distortion calibration obtained by a full camera calibration method which uses a calibration grid. Received: 27 December 1999 / Accepted: 8 November 2000     

一种基于模糊阈值的直线拟合策略在铁路沿线柱体检测及距离估计中的应用

首先提出了一种单幅图像中由边缘检测自动估计铁路沿线柱体到铁轨大致距离的方法，该方法主要通过对铁轨及其沿线柱体的检测、分类识别和距离估计来完成。因为如何在有畸变和复杂背景的图像中准确和有效检测边缘在图像处理和模式识别中一直是一个关键而困难的问题，为此提出了一种基于模糊阈值的直线连接拟合策略，该策略主要包括3个步骤：边缘提取、角点检测和基于模糊阈值的直线递归拟合。该策略可以有效地在有图像畸变和复杂背景的实际拍摄图片中通过参数控制获取感兴趣目标的直线边界。实验结果证明本文的直线拟合策略是精确的和具有鲁棒性的，距离估计方法是有效的。     

参数控制的边缘直线提取算法

提出了在灰度图像上使用参数控制的边缘直线提取算法，解决了图像理解过程中高效地提取边缘直线这一困难的问题。在计算出直线位置和方向的基础上，还能够计算直线的对比度、宽度、倾斜度等属性。实验显示，算法速度快、精度高、提取结果信息量丰富。     

一种基于Curvelet变换的红外图像去噪方法

小波变换在分析二维图像中曲线或者直线边缘特征方面存在明显不足,用于红外图像去噪中没有较好的逼近精度和稀疏表达能力。为解决上述问题,提出一种基于Curvelet变换的阈值改进算法,即采用软硬阈值结合的方式,形成新的阈值函数。通过对可见光和红外图像进行仿真实验。结果表明,该方法与正交小波去噪以及软硬阈值去噪算法相比,在去噪和保持边缘的同时,取得了较好的红外视觉效果,并且峰值信噪比PSNR也得到一定的提高。     

Preliminary coarse image registration by using straight lines found on them for constructing super resolution mosaics and 3D scene recovery

An algorithm of coarse image registration of a 3D scene taken from different camera perspectives is proposed. The algorithm uses information on geometrical parameters of straight lines found on the images and on distribution of color and/or brightness around these lines. Colors are taken into account by using the fuzzy logic technique. The result of the algorithm operation is a planar projective transformation (planar homography) matching approximately the images. In order to use the technique in algorithms of 3D scene reconstruction, an estimate of size of the window used for searching correspondent points after the coarse image registration is obtained.     

基于第2代Curvelet变换的彩色图像去噪

提出基于第2代Curvelet变换的彩色图像去噪算法,克服小波变换在表达彩色图像边缘的方向特性等方面的内在缺陷。该算法适合分析二维彩色图像中的曲线或直线状边缘特征,且具有较高的逼近精度和稀疏表达能力。通过Matlab对512×512的Lena和Babon彩色图像进行仿真实验,结果表明,该算法在视觉效果和性能指标方面都优于小波和Ridgelet算法。     

A generative sketch model for human hair analysis and synthesis

In this paper, we present a generative sketch model for human hair analysis and synthesis. We treat hair images as 2D piecewise smooth vector (flow) fields and, thus, our representation is view-based in contrast to the physically-based 3D hair models in graphics. The generative model has three levels. The bottom level is the high-frequency band of the hair image. The middle level is a piecewise smooth vector field for the hair orientation, gradient strength, and growth directions. The top level is an attribute sketch graph for representing the discontinuities in the vector field. A sketch graph typically has a number of sketch curves which are divided into 11 types of directed primitives. Each primitive is a small window (say 5 /spl times/ 7 pixels) where the orientations and growth directions are defined in parametric forms, for example, hair boundaries, occluding lines between hair strands, dividing lines on top of the hair, etc. In addition to the three level representation, we model the shading effects, i.e., the low-frequency band of the hair image, by a linear superposition of some Gaussian image bases and we encode the hair color by a color map. The inference algorithm is divided into two stages: 1) We compute the undirected orientation field and sketch graph from an input image and 2) we compute the hair growth direction for the sketch curves and the orientation field using a Swendsen-Wang cut algorithm. Both steps maximize a joint Bayesian posterior probability. The generative model provides a straightforward way for synthesizing realistic hair images and stylistic drawings (rendering) from a sketch graph and a few Gaussian bases. The latter can be either inferred from a real hair image or input (edited) manually using a simple sketching interface. We test our algorithm on a large data set of hair images with diverse hair styles. Analysis, synthesis, and rendering results are reported in the experiments.