一种多视图分层重构算法研究

本文介绍了基于奇异值分解的射影重构算法的一般框架,以测量矩阵的秩为4作为约束,以仿射投影逼近透视投影,利用共轭梯度法估计射影深度,通过奇异值分解实现射影重构.利用共轭梯度法确定Kruppa方程中的未知比例因子,然后利用所确定的比例因子线性求解Kruppa方程,进而标定摄像机内参数.在摄像机内参数已知的情况下,求解一个满足欧氏重构条件的非奇异矩阵,然后通过此矩阵将射影重构变换为欧氏重构.实验结果表明所给出的算法是行之有效的.     

基于遗传算法的射影重构

在实现分层重构的过程中，射影重构是关键的第1步。目前，大多已有算法对模拟数值是非常有效的，但对于真实图象效果并不理想。为了寻求更为鲁棒的算法，提出了一种基于遗传算法的射影重构算法。该算法对于射影深度采用十进制编码，并以测量矩阵的秩为4作为约束，来定义适应度函数，然后利用遗传算法，并结合奇异值分解（SVD）技术来迭代估计射影深度，进而实现射影重构，该算法是行之有效的，且鲁棒性较好。     

基于外点检测与校正的填充射影分解算法

针对三维重构中存在的数据缺失和遮挡问题,提出可处理缺失数据的填充射影分解算法,利用子空间约束与对极几何约束进行矩阵拟合并填充缺失数据,通过奇异值分解得到射影运动与结构参数。为克服该算法对噪声和外点的敏感性,结合RANSAC算法和三角形法对其进行外点检测与校正。实验结果表明,加入外点校正后的算法可提高射影重构的鲁棒性,降低误差,具有较高的实用价值。     

基于鲁棒迭代优化的图像拼接算法

针对保持直线边缘不畸变和改善拼接区域精度的需要,提出了一种基于鲁棒迭代优化的图像拼接算法。采用SIFT特征匹配算法提取不变特征,依据RANSAC鲁棒算法估计单应性矩阵获取精确内点匹配点对,参照内点匹配点对作为参数,利用最小二乘法重新估计单应性矩阵,最终通过鲁棒迭代优化重新计算更多内点直至内点收敛。实验结果表明,所提出的算法使得直线边缘维持直线化,同时拼接精度得到提高。     

基于统计优化的单应矩阵估计算法

计算机科学中研究的图像是真实世界(即二维、三维欧式空间)到像平面的射影变换.平面射影变换(单应)估计是特征目标检测、注册、识别、三维重建等方面的关键步骤,但是如何鲁棒、精确地估计单应矩阵是一个没有很好解决的问题.在研究中发现,基于点与直线的直接的单应矩阵估计方法会导致出现较大误差的情况.针对这一情况,文中介绍了一种基于统计优化的单应矩阵估计方法,这种方法是通过单应矩阵的协方差张量的计算和优化来估计单应矩阵的.最后进行了简单的实验,比较了统计优化方法与进行归一化处理后的直接线性方法的估计结果,证明了基于优化统计的估计方法更加有效     

一种非定标图像高精度三维重建算法

由非定标图像重建三维场景有着广泛的应用。给出了一种非定标多视图像三维重建算法。该算法主要基于因子分解和光束法平差技术。首先用因子分解方法得到射影空间下相机投影矩阵和物点坐标,以旋转矩阵的正交性以及对偶绝对二次曲面秩为3为约束,将射影空间升级到欧式空间,最后用光束法平差进行优化。该方法可同时获得相机的内外参数、畸变系数和场景的三维坐标。仿真实验表明,在1000 mm×1000 mm×400mm的范围内,当像点检测误差在0-1pixel和0-2pixel内,所重建三维点的误差分别为0.1530 mm和0.6712 mm。在500 mm×500 m×200 mm下,真实实验重构三维点的误差在0.3 mm以内。所提出的算法稳定可靠,可对实际工程进行指导。     

一种高精度鲁棒的基于直线对应的位姿估计迭代算法

2D-3D特征对应位姿估计问题算法多基于点对应,而基于直线对应求解比基于点对应求解更具有优势。从欧氏空间这一新颖角度出发,提出了一种从直线对应求解位姿估计问题的迭代算法,算法思想是先迭代求解出最优的旋转矩阵,然后再得到平移向量。针对不同的直线组情形,给出了相应的迭代初始值计算方法。仿真实验数据表明,算法具有对初始值较不敏感、高精度、鲁棒性好等特点。     

基于射影空间的视觉基础矩阵鲁棒估计

针对传统视觉基础矩阵计算中存在的噪音和误匹配问题,提出了基于射影空间的基础矩阵计算方法．首先定义了三视几何中射影标准基下基础矩阵只含有5个参数的特殊形式,并利用三视射影重建中空间点反投影图像误差最小为准则,消除了图像中误匹配的影响,然后基于RANSAC(random sampling consensus)技术寻找出最优7个匹配点（噪音最小）来进行对极几何估算．大量仿真模拟试验和真实图像表明此方法能够高精度地估计出基础矩阵．     

基于SVD的二维子空间拟合DOA估计

改进传统子空间拟合波达方向(DOA)估计方法,以快拍数据矩阵的奇异值分解代替接收数据协方差矩阵的特征值分解,用奇异值和奇异值矢量进行信源数估计,避免协方差矩阵估计,减少运算量和矩阵估计误差。根据已有子空间拟合的一维修正变化投影(MVP)算法原理,推导出二维MVP算法实现步骤,对基于均匀圆阵的接收信号进行二维DOA估计。     

线性多视图重构的新算法

研究了由多幅图像恢复摄像机矩阵和空间物体三维几何形状这一多视图三维重构问题,改进了由Hartley和Rother等人分别给出的基于由无穷远平面诱导的单应进行射影重构的算法,提出了一种新的线性算法,它仅需要空间中3个点在每幅图像上均可见。因为空间中不在同一直线上的3个点恰好确定一个平面,所以它避免了Hartley和Rother等方法中需要确定空间4个点是否共面这一比较棘手的问题。大量实验结果表明,这种方法快速、准确且受噪声影响小。     

一种鲁棒性的射影重建方法--加权迭代法

本文提出了一种利用加权迭代来剔除出格数据并实现射影重建的方法,该方法首先利用加权来进行射影重建,再利用重投影误差的倒数作为下一次迭代的权值,如此循环,就可以使出格数据的权值接近于0,最后完成射影重建.本方法可以克服最小二乘法鲁棒性差及随机抽样算法计算量大的缺点,模拟实验和真实实验数据结果表明,该重建方法具有运算量小、鲁棒性好等优点.     

Affine structure from line correspondences with uncalibrated affinecameras

This paper presents a linear algorithm for recovering 3D affine shape and motion from line correspondences with uncalibrated affine cameras. The algorithm requires a minimum of seven line correspondences over three views. The key idea is the introduction of a one-dimensional projective camera. This converts 3D affine reconstruction of “line directions” into 2D projective reconstruction of “points”. In addition, a line-based factorization method is also proposed to handle redundant views. Experimental results both on simulated and real image sequences validate the robustness and the accuracy of the algorithm     

Reconstructing camera projection matrices from multiple pairwise overlapping views

In this work we address the problem of projective reconstruction from multiple views with missing data. Factorization based algorithms require point correspondences across all the views. In many applications this is an unrealistic assumption. Current methods that solve the problem of projective reconstruction with missing data require correspondence information across triplets of images. We propose a projective reconstruction method that yields a consistent camera set given the fundamental matrices between pairs of views without directly using the image correspondences. The algorithm is based on breaking the reconstruction problem into small steps. In each step, we eliminate as much uncertainty as possible.     

基于秩4约束的遮挡点恢复方法

提出了一种基于秩4约束的遮挡点恢复方法.该方法 首先假设所有的遮挡点及深度因子已知,利用所有遮挡点及深度因子组成一个秩4矩阵的特 性,构造一个投影矩阵,并利用该投影矩阵求得所有的遮挡点及深度因子.然后将求得的遮 挡点及深度因子代替图像中的遮挡点和深度因子,再求投影矩阵.经过多次迭代,最后求得 遮挡点的真实图像位置.该方法的优点是平等地看待所有的图像及图像点.模拟实验和真实实 验表明,该方法具有鲁棒性好、收敛性好及误差小等优点.     

Line Clipping Using Semi-Homogeneous Coordinates

The dual intersection test is described. It is a new method for deciding whether a line intersects a window. The concept of semi-homogeneous coordinates is introduced. It allows us to define line segments in projective space, and to derive a generalized Cohen-Sutherland end-point test for such segments. When this is combined with the dual intersection test, we obtain new clipping algorithms for 2D and 3D projective space.     

A new approach to 3D reconstruction without camera calibration

In this paper, we present a new approach for 3D scene reconstruction based on projective geometry without camera calibration. Previous works use at least six points to build two projective reference planes. Our contribution is to reduce the number of reference points to four by exploiting some geometrical shapes contained in the scene. The first implemented algorithm allows the reconstruction of a fourth point on each reference plane. The second algorithm is devoted to the 3D reconstruction. We obtained the expected good results and the proposed method is to equip a mobile robot moving in a structured environment.     

Conic reconstruction and correspondence from two views

Conics are widely accepted as one of the most fundamental image features together with points and line segments. The problem of space reconstruction and correspondence of two conics from two views is addressed in this paper. It is shown that there are two independent polynomial conditions on the corresponding pair of conics across two views, given the relative orientation of the two views. These two correspondence conditions are derived algebraically and one of them is shown to be fundamental in establishing the correspondences of conics. A unified closed-form solution is also developed for both projective reconstruction of conics in space from two uncalibrated camera views and metric reconstruction from two calibrated camera views. Experiments are conducted to demonstrate the discriminality of the correspondence conditions and the accuracy and stability of the reconstruction both for simulated and real images