鱼眼镜头的标定和畸变校正研究

为在使用鱼眼镜头得到大视野图像的同时得到正常的视觉效果,研究鱼眼镜头的成像模型及内外参数的标定过程.相比常用的标定算法,采用基于镜头模型的标定方法;针对Davide Scaramuzza提出的全方位相机标定工具箱,指出其不足之处,对角点坐标的精度、标定系数矩阵稳定性和角点范围随意性三方面进行优化和提高;根据标定结果对鱼眼畸变图像进行畸变校正,得到正常视觉的平面图.实验结果表明,优化后的方法实现简单、鲁棒性强、结果准确.     

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。     

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。     

基于三线结构光的相机平面标定方法研究

相机标定技术是结构光三维视觉测量的关键技术之一,结构光测量系统的相机标定的精度对三维测量的精度有很大影响;首先对三线结构光系统图的相机标定方法进行了分析,简单介绍了工业相机成像的几何模型及标定的原理;其次利用Harris角点检测方法提取特征点坐标,并选用了BP神经网络来校正工业相机的畸变模型,以提高标定算法的优化速度和标定精度;最后采用张正友的平面标定法对校正后的摄像机模型进行标定实验,由实验结果知,该方法具有一定的准确性和有效性,在一定误差范围内,基于神经网络畸变校正的张正友相机标定能够有效提高视觉检测的精度。     

3D靶标的摄像机三步标定算法与实现

摄像机标定是计算机视觉中的一个必不可少的重要环节,其标定精度影响着三维重建结果的精度。利用摄像机对一个三维正交的棋盘格拍摄一幅有效靶标图像,提取角点,第一步通过透视变换矩阵算法线性求解各内外参数;第二步引入径向和切向畸变,将第一步求得的内外参数作为初始值,求得畸变系数的解;第三步对内参数进行线性优化,得到更为精确的内参数值;最后求解反投影后图像坐标的绝对误差。实验结果表明,该方法具有较高的精度,且简单有效。     

3D靶标的摄像机三步标定算法与实现

摄像机标定是计算机视觉中的一个必不可少的重要环节,其标定精度影响着三维重建结果的精度。利用摄像机对一个三维正交的棋盘格拍摄一幅有效靶标图像,提取角点,第一步通过透视变换矩阵算法线性求解各内外参数;第二步引入径向和切向畸变,将第一步求得的内外参数作为初始值,求得畸变系数的解;第三步对内参数进行线性优化,得到更为精确的内参数值;最后求解反投影后图像坐标的绝对误差。实验结果表明,该方法具有较高的精度,且简单有效。     

CCD摄像机标定的研究

在计算机视觉中,二维计算机坐标和三维物体空间坐标的关系可通过摄像机模型来建立.模型中的参数包括:摄像机几何、光学特性参数(内参数)及摄像机空间位置参数(外参数).摄像机的标定就是要确定这些参数.本文分析了三维空间点投影在像平面的像点产生畸变的原因:在大视场摄像机镜头各向同性,而且物像空间媒质均匀的情况下,像素单位元面积产生的变化引起像点畸变,并在实际图像坐标到计算机图像(帧存)坐标标定过程中推导出CCD传感器单元N方向的比例系数N<,x>的表达式,并进行了实验测量分析,取得的结果对提高标定精度具有意义.     

基于等间距线的几何畸变校正

摄像机视觉测量系统中图像存在几何畸变,会降低尺寸测量精度,必须进行校正.目前基于单张图像的畸变校正方法主要有标定板特征点转移矩阵的非参数化方法和利用特征点共线性或无穷点约束条件的参数化方法,由于上述方法需要获取多个特征点的坐标,而获取孤立的坐标点容易造成误差,使得校正效果不好.提出采用等间距线方法,利用畸变模型建立间距...     

基于投影变换的图像测量系统标定

图像测量系统标定是计算机视觉获取三维信息的前提和基础。为了进一步提高标定精度和速度,提出了一种新的基于投影变换标定法。首先,构造模版图像,将该图像经投影变换得到无畸变图像,然后,将其与由原始图像经消除畸变后所得的无畸变图像进行对比,通过差值来确定畸变模型系数。在求出畸变模型的基础上,再求解其他相机参数。该方法迴避了传统方法繁多的迭代步骤,避免了由于初始参数的估计不准所产生的误差,具有直观、精确和相对快速等优点。并通过实验仿真,验证了该算法的可行性与准确性。     

双目立体摄像机标定方法研究

本文在张正友平面模板两步法的基础上,提出了一种改进的双目立体摄像机标定方法。该方法在摄像机畸变模型中充分考虑了切向畸变的影响,使得应用范围更广。本文在标定中通过选取图像中心附近的点作为初始预测值,再进行非线性搜索来确定摄像机内外参数。实验证明,本文标定模板制作简单,标定过程快捷,且具有较高的精度,完全可以满足双目立体视觉应用的要求。     

基于平板探测器倾斜的锥束CT修正重建算法

在锥束工业CT系统中要求射线源焦点,物体旋转中心,平板探测器中心三点在一条直线上,但由于机械的定位误差,探测器定位后会出现一定角度的倾斜现象,如果平板探测器直接采集投影数据进行重建,重建结果将会出现偏离,产生伪影.针对该问题,使用系统标定的方法测得探测器倾斜角度,并用机械校正对其进行粗调,利用平板探测器倾斜的FDK修正算法进行微调,经过两次校正可以有效的抑制由于倾斜造成的伪影,通过实验验证了该方法的有效性和可行性.     

近距离多目标（种子）检测中摄像机系统的标定方法

在进行基于计算机视觉的排种器性能检测时，为了解决目标（种子）之间的遮挡、加快图象采集速度和节省计算机的存储空间，提出了一种近距离多目标（种子）检测中，摄像机系统的标定方法。建立了由摄像机和平面镜组成的摄像机系统标定的数学模型，并给出了恢复空间点的方法。同时在排种器实验台上进行了验证，结果表明该系统不仅能较好地检测出种子和重叠和丢失等情况，而且检测误差小于1mm，且完全可以不用粘胶带，即可检测出排种器性能。     

Cylindrical panoramic mosaicing from a pipeline video through MRF based optimization

Stratum structure detection is a fundamental problem in geological engineering. One of the most commonly employed detection technologies is to shoot videos of a borehole using a forward moving camera. Using this technology, the problem of stratum structure detection is transformed into the problem of constructing a panoramic image from a low quality video. In this paper, we propose a novel method for creating a panoramic image of a borehole from a video sequence without the need of camera calibration and tracking. To stitch together pixels of neighboring image frames, our camera model is designed with a focal length changing feature, along with a small rotational freedom in the two-dimensional image space. Our camera model assumes that target objects lie on a cylindrical wall and that the camera moves forward along the central axis of the cylindrical wall. Based on these two assumptions, our method robustly resolves these two degrees-of-freedoms in our camera model through KLT feature tracking. Since the quality of the result video is affected by possible illumination overflow, camera lens blurring, and low video resolution, we introduce a cost function for eliminating seams between stitching strips. Our cost function is designed based on Markov Random Field and optimized using a belief propagation algorithm. Using our method, we can automatically construct a panorama image with good resolution, smoothness, and continuousness both in the texture and illumination space. Experiment results show that our method could efficiently generate panoramas for long video sequences with satisfying visual quality.     

Pose Estimation using Point and Line Correspondences

The problem of a real-time pose estimation between a 3D scene and a single camera is a fundamental task in most 3D computer vision and robotics applications such as object tracking, visual servoing, and virtual reality. In this paper we present two fast methods for estimating the 3D pose using 2D to 3D point and line correspondences. The first method is based on the iterative use of a weak perspective camera model and forms a generalization of DeMenthon's method (1995) which consists of determining the pose from point correspondences. In this method the pose is iteratively improved with a weak perspective camera model and at convergence the computed pose corresponds to the perspective camera model. The second method is based on the iterative use of a paraperspective camera model which is a first order approximation of perspective. We describe in detail these two methods for both non-planar and planar objects. Experiments involving synthetic data as well as real range data indicate the feasibility and robustness of these two methods. We analyse the convergence of these methods and we conclude that the iterative paraperspective method has better convergence properties than the iterative weak perspective method. We also introduce a non-linear optimization method for solving the pose problem.     

A closed form for low-order panel methods

A closed form for the computation of the dipolar and monopolar influence coefficients related to a low-order panel method is shown. The flow problem is formulated by means of a three-dimensional potential model; the method of discretization is based on the Morino formulation for the perturbation velocity potential. On the body surface this representation reduces to an integral equation with the source (or monopolar) and the doublet (or dipolar) densities. The former is found by application of the boundary condition, and the latter is the unknown over the surface of the body. The lower panel method is used for the analytical integrations of the monopolar and dipolar influence coefficients, with special attention to avoid a logarithmic singularity in the monopolar matrix when flat fairly structured meshes that are common in ship-wave calculations are used.     

Spatial-temporal consistent labeling of tracked pedestrians across non-overlapping camera views

Tracking people across multiple cameras with non-overlapping views is a challenging task, since their observations are separated in time and space and their appearances may vary significantly. This paper proposes a Bayesian model to solve the consistent labeling problem across multiple non-overlapping camera views. Significantly different from related approaches, our model assumes neither people are well segmented nor their trajectories across camera views are estimated. We formulate a spatial-temporal probabilistic model in the hypothesis space that consists the potentially matched objects between the exit field of view (FOV) of one camera and the entry FOV of another camera. A competitive major color spectrum histogram representation (CMCSHR) for appearance matching between two objects is also proposed. The proposed spatial-temporal and appearance models are unified by a maximum-a-posteriori (MAP) Bayesian model. Based on this Bayesian model, when a detected new object corresponds to a group hypothesis (more than one object), we further develop an online method for online correspondence update using optimal graph matching (OGM) algorithm. Experimental results on three different real scenarios validate the proposed Bayesian model approach and the CMCSHR method. The results also show that the proposed approach is able to address the occlusion problem/group problem, i.e. finding the corresponding individuals in another camera view for a group of people who walk together into the entry FOV of a camera.     

The effects of temperature variation on videometric measurement and a compensation method

When a videometric system operates over a long period, temperature variations in the camera and its environment will affect the measurement results, which cannot be ignored. How to eliminate or compensate for the effects of such variations in temperature is an emergent problem. Starting with the image drift phenomenon, this paper presents an image-drift model that analyzes the relationship between variations in the camera parameters and drift in the coordinates of the image. A simplified model is then introduced by analyzing the coupling relationships among the variations in the camera parameters. Furthermore, a model of the relationship between the camera parameters and temperature variations is established with the system identification method. Finally, several compensation experiments on image drift are carried out, using the parameter–temperature relationship model calibrated with one arbitrary data set to compensate the others. The analyses and experiments demonstrate the feasibility and efficiency of the proposed method.     

Visual tracking control for an uncalibrated robot system with unknown camera parameters

The robust trajectory tracking problem for an eye-in-hand system is addressed in this paper. A novel visual feedback control model is proposed. It considers not only the uncertainties and disturbances in the robot model, but also the unknown camera parameters. By using sliding mode control, filter method and adaptive technique, the controller is designed such that the robot can track the desired trajectory well by using information provided by camera. Finally, stability and robustness are rigorously proved by using Lyapunov method. Computer simulations are presented to show the effectiveness of the proposed visual feedback controller.     

VCode—Pervasive Data Transfer Using Video Barcode

In this paper, we describe a novel data transfer scheme that uses the camera in a smart phone as an alternative data channel. The data is encoded as a sequence of 2-D barcode images, displayed on a flat panel display, acquired by the camera, and decoded in real time by the software embedded in device. The decoded data is written to a file. Compared with existing data channels, such as CDMA/GPRS, cables, Bluetooth, and Infrared, our method relies on visual communication and does not require special hardware or data plans. Users only need to point the camera at a monitor displaying the VCode to download. Technical challenges to overcome include correction of perspective distortion, compensation for contrast variation, and efficient implementation of small footprint software into a mobile device. We address these challenges and present our solution in detail. We have implemented a prototype which allows users to download various types of files successfully, including pictures, ring tones and Java games onto camera phones running Symbian and Windows Mobile platforms. We discuss the limitations of our solution and outline future work to overcome these limitations.     

一种基于TOF相机与CCD相机的联合标定算法研究

针对基于Time-of-Flight(TOF)相机的彩色目标三维重建需标定CCD相机与TOF相机联合系统的几何参数,在研究现有的基于彩色图像和TOF深度图像标定算法的基础上,提出了一种基于平面棋盘模板的标定方法。拍摄了固定在平面标定模板上的彩色棋盘图案在不同角度下的彩色图像和振幅图像,改进了Harris角点提取,根据棋盘格上角点与虚拟像点的共轭关系,建立了相机标定系统模型,利用Levenberg-Marquardt算法求解,进行了标定实验。获取了TOF与CCD相机内参数,并利用像平面之间的位姿关系估计两相机坐标系的相对姿态,最后进行联合优化,获取了相机之间的旋转矩阵与平移向量。实验结果表明,提出的算法优化了求解过程,提高了标定效率,能够获得较高的精度。