基于单幅折反射全向图的水平直线3维重建

与传统的利用立体视觉原理进行3维重建不同,在研究基于单幅全向图像重建空间水平直线问题的基础上,首先指出基于直线在全向图中的两个像点即可重建该水平直线,然后通过分析和推导空间水平直线在全向成像系统中的成像特点,有效简化了全向图中的水平直线检测;针对现有“四点定位”方法的不足,提出了一种基于“主像点/非主像点”的水平直线重建算法,并详细分析了像点提取精度对直线重建结果的影响。实验表明,在不同的像点提取精度下,对于不同空间水平直线,该重建算法均能取得较好结果。     

基于单幅全向图像的空间水平直线定位新方法

研究了在没有先验知识的前提下,基于单幅全向图像定位空间水平直线的问题.在已有算法的基础上,分析和推导了空间水平直线在全向成像系统中的成像特点,指出基于直线在全向图中的两个像点即可重建该水平直线,并相应地提出了一种基于"主像点/非主像点"的空间水平直线定位算法.试验表明,在不同的像点提取精度下,对于不同空间水平直线,本方法均能取得较好结果.     

Three-Dimensional Reconstruction of Points and Lines with Unknown Correspondence across Images

Three-dimensional reconstruction from a set of images is an important and difficult problem in computer vision. In this paper, we address the problem of determining image feature correspondences while simultaneously reconstructing the corresponding 3D features, given the camera poses of disparate monocular views. First, two new affinity measures are presented that capture the degree to which candidate features from different images consistently represent the projection of the same 3D point or 3D line. An affinity measure for point features in two different views is defined with respect to their distance from a hypothetical projected 3D pseudo-intersection point. Similarly, an affinity measure for 2D image line segments across three views is defined with respect to a 3D pseudo-intersection line. These affinity measures provide a foundation for determining unknown correspondences using weighted bipartite graphs representing candidate point and line matches across different images. As a result of this graph representation, a standard graph-theoretic algorithm can provide an optimal, simultaneous matching and triangulation of points across two views, and lines across three views. Experimental results on synthetic and real data demonstrate the effectiveness of the approach.An erratum to this article can be found at     

A way to detect the straight line trajectory of an immovable point for estimating parameters of geometrical transformation of 3D images

When 3D images are matched by using the immovable point method, the problem of detecting the straight lines in the binary 3D image that consists of points suspicious for immobility occurs. True immovable points are a thin approximately straight line being among the chaotically dispensing points. False straight line trajectories, which are parallel to the true one, are also possible. In this work a procedure for searching all straight lines in 3D binary images and detecting the true trajectory among them is described.     

分层点云的分段化

说明一种点云的分段算法.这是从点云重建立体造型的关键步骤.假设原对象是以平面和二次曲面为边界,且点云是分布在一些平行平面的层上.提出的算法是基于从一维流形发展到二维流形的策略.首先在每一层上识别二次曲线和直线,把位于相邻层且有相同固有属性的二次曲线或直线分成组,每一组内的二次曲线或直线位于同一个二次曲面或平面上.给出了3个例子说明该算法的效果.该方法可用于逆向工程构造产品的立体造型.     

折反射全向图像与遥感图像配准的建筑物高度提取算法

提出一种折反射全向图像与遥感图像配准的建筑物高度提取算法,可应用于大范围三维城市重建。首先,利用全向Hough变换方法提取折反射全向图像中建筑物的顶部边界线;然后基于提取的边界线,根据空间水平直线全向成像的角度不变性对折反射全向图像与遥感图像进行配准;最后利用配准结果,依据折反射全向图成像模型计算建筑物高度。实验结果证明该方法简捷易行且计算结果准确,误差较小。     

Line Localization from Single Catadioptric Images

Indoor environments often contain several line segments. The 3D reconstruction of such environments can thus be reduced to the localization of lines in the 3D space. Multi-view reconstruction requires the solution of the correspondence problem. The use of a single image to localize space lines is attractive, since the correspondence problem can be avoided. However, using a central camera the line localization from single image is an ill-posed problem, because there are infinitely many lines sharing the same image.     

数字曲线切点检测技术

针对数字曲线的切点识别问题,提出一种基于转角累加的数字曲线切点检测技术。该技术对数字曲线进行光顺处理,构造转角累加线、转角累加线曲率线和曲率波,通过对相邻的分段逼近直线求交确定切点位置。实验结果表明,该方法切点识别准确、迅速,对于由直线、圆弧组成的轮廓边界能实现准确分段。     

单视未标定图像的正交灭点检测算法

传统方法只能计算标定图像的正交灭点,同时没有考虑图像直线检测结果的误差、 直线的长度以及候选灭点与约束直线之间的位置关系对灭点检测精度的影响。针对此类问题, 提出了一种针对单视未标定图像的正交灭点检测方法。首先利用J-Linkage 完成灭点的初始化估 计,得到假设灭点集合;然后根据假设灭点与图像直线之间的一致性约束、图像直线的长度, 基于投票机制先得到精确的垂直方向灭点;后利用灭点、灭线的定义和性质,计算得到图像相 机参数;根据正交灭点的特性,得到准确的水平方向和纵深方向的灭点。因引入了一种新的假 设灭点和图像直线之间的一致性度量方法,正交灭点检测精度不受直线检测结果的误差、直线 的长度以及候选灭点与约束直线之间的位置关系的影响,在未知图像相机参数的情况下能精准 的得到三个正交灭点信息。正交灭点检测方法在室内场景下可以得到更加精确的检测结果。     

Improving three-dimensional point reconstruction from image correspondences using surface curvatures

Recovering three-dimensional (3D) points from image correspondences is an important and fundamental task in computer vision. Traditionally, the task is completed by triangulation whose accuracy has its limitation in some applications. In this paper, we present a framework that incorporates surface characteristics such as Gaussian and mean curvatures into 3D point reconstruction to enhance the reconstruction accuracy. A Gaussian and mean curvature estimation scheme suitable to the proposed framework is also introduced in this paper. Based on this estimation scheme and the proposed framework, the 3D point recovery from image correspondences is formulated as an optimization problem with the surface curvatures modeled as soft constraints. To analyze the performance of proposed 3D reconstruction approach, we generated some synthetic data, including the points on the surfaces of a plane, a cylinder and a sphere, to test the approach. The experimental results demonstrated that the proposed framework can indeed improve the accuracy of 3D point reconstruction. Some real-image data were also tested and the results also confirm this point.     

基于医学图像的复杂曲面重建

为了更准确地重建复杂的三维医学数据模型,把二维医学图像轮廓线上的像素点转化为三维点云,引入经典的泊松点云重建技术。由于泊松重建的效果依赖于点云法向的准确性,针对轮廓线数据的特点,结合图像二维梯度方向,给出了点云法向的一致定向及基于已知定向进一步精确估计法向的方法。泊松重建方法作为一种隐式重建技术,可以很好地处理医学图像数据中经常存在的噪声、拓扑复杂等问题。鼻咽喉模型重建的结果说明,一致定向方法改进了传统的一致定向方法,得到了更为准确的医学重建模型。     

基于标记点丢失的多幅自标定图像的3维重建和相机姿态恢复

为了对标记点丢失的多幅自标定图像进行精确重建，提出了一种基于标记点丢失的多幅自标定图像的3维重建和相机姿态恢复的方法。该方法与原来方法的不同之处在于，该方法是利用标记点（编码点和非编码点）的方式，即用编码点进行单CCD相机的自标定和姿态恢复，而用非编码点进行3维点的3维重建。该方法有以下3个主要特点：（1）由于该方法采用了标记点的自动识别匹配，所以避免了手工交互选择图像点对（point correspondences）费工费时的问题；（2）由于标记点匹配精确，提高了3维点的重建精度，故符合工程要求；（3）由于噪音对标记点的像点影响较小，因此该方法比以前的方法具有更好的鲁棒性。实验结果表明，利用该方法产生的3维重建点精确可靠，能够满足逆向工程等应用的要求。     

Shape recovery from turntable sequence using rim reconstruction

This paper makes use of both feature points and silhouettes to deliver fast 3D shape recovery. The algorithm exploits object silhouettes in two views to establish a 3D rim curve, which is defined with respect to the two frontier points arising from two views. The images of this 3D rim curve in the two views are matched using cross-correlation technique. A 3D planar rim curve is then reconstructed using point-based reconstruction method. A set of 3D rim curves enclosing the object can be obtained from an image sequence captured under circular motion. Silhouettes are further utilized to check for mismatched rim points. The proposed method solves the problem of reconstruction of concave object surface, which is usually left unresolved in general silhouette-based reconstruction methods. In addition, the property of the reconstructed 3D rim curves allows fast surface extraction. Experimental results with real data are presented.     

Trajectory triangulation: 3D reconstruction of moving points from amonocular image sequence

We consider the problem of reconstructing the 3D coordinates of a moving point seen from a monocular moving camera, i.e., to reconstruct moving objects from line-of-sight measurements only. The task is feasible only when some constraints are placed on the shape of the trajectory of the moving point. We coin the family of such tasks as “trajectory triangulation.” We investigate the solutions for points moving along a straight-line and along conic-section trajectories, We show that if the point is moving along a straight line, then the parameters of the line (and, hence, the 3D position of the point at each time instant) can be uniquely recovered, and by linear methods, from at least five views. For the case of conic-shaped trajectory, we show that generally nine views are sufficient for a unique reconstruction of the moving point and fewer views when the conic is of a known type (like a circle in 3D Euclidean space for which seven views are sufficient). The paradigm of trajectory triangulation, in general, pushes the envelope of processing dynamic scenes forward. Thus static scenes become a particular case of a more general task of reconstructing scenes rich with moving objects (where an object could be a single point)     

图像的平视化处理

摄像机拍摄图像时,会使物体在同一水平面上的边缘呈现曲线形状,给图像处理方法的实现和图像边缘位置的定位带来不便。这篇文章研究了把图像的曲线边缘变为直线边缘的图像平视化处理方法,推导了像素点和空间点的对应关系公式,陈述了图像平视化处理的思路,并对现场采集的图像进行了平视化处理。通过试验,这篇文章的平视化方法取得了较好的效果。     

基于 2 个灭点和局部尺度的三维空间尺度估计

三维空间尺度估计是三维重建中的一个重要工作,现实世界中也存在一些基于单幅图像进行三维空间尺度估计的需求。通常情况下,尺度估计需先对相机进行标定。根据单目图像符合透视原理的特性,提出了一种基于 2 个灭点和局部尺度信息的方法对相机进行标定,从而得到单目图像物体中三维空间尺度信息的估计。首先,从单目图像中选择 2 组互相正交的平行线组,得到对应 2 个灭点的坐标;然后,利用灭点坐标和焦距信息得到世界坐标系和相机坐标系之间的旋转矩阵,再利用灭点的性质和已知局部尺度信息得到平移向量,完成单目相机的标定;最后,还原二维图像中像素点对应的三维世界坐标值,计算出图像中 2 个像素点在三维空间的尺度信息。实验结果表明,该方法能有效地对单幅图像中的建筑物体进行尺度估计。     

基于对称物体的3维重构技术研究

3维重构理论与技术是计算机视觉领域最重要的热点问题之一,而基于单幅图像的3维重构由于缺乏足够的几何信息而难以达到预期效果,已成为世纪性难题。针对大部分物体具有对称性特征,或可分解为有限个对称物体元的客观事实,提出基于透视逆变换原理,首先建立包含摇角、倾角、摆角等三元的透视变换矩阵T;再由链码表示的物体轮廓提取特征直线,根据平行线束投影角相近性特点求解主灭点信息,进而确定视点位置、物体对称平面;根据对称性特征,利用物体假想对称平面,通过人工交互指定3对已知对称点的图像坐标及其对应点的空间坐标确定透视变换矩阵T,继而反求物体表面其他特征点的空间位置,最后利用OpenGL软件包实现物体3维模型的重建。     

3D-ARNet: An accurate 3D point cloud reconstruction network from a single-image

Multimedia Tools and Applications - Generating a more realistic 3D reconstruction point cloud is an ill-posed problem. It is a challenging task to infer 3D shape from a single image. In this paper,...     

基于直线光流场的三维运动和结构重建

利用直线间运动对应关系，将像素点光流的概念和定义方法应用于直线，提出了直线光流的概念，建立了求解空间物体运动参数的线性方程组，利用三幅图像21条直线的光流场，可以求得物体运动的12个参数以及空间直线坐标．但是在实际应用当中，要找出这21条直线的光流场是很困难的，因此该文提出了运用解非线性方程组的方法，只需要6条直线的光流．就可以分步求出物体的12个运动参数，并根据求得的12个运动参数和一致的图像坐标系中的直线坐标，求得空间直线的坐标，从而实现了三维场景的重建．