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Gandalf软件（含源码）主要用于计算机视觉分析与相关数字分析。用C语言编写。Gandalf is a computer vision and numerical algorithm library, written in C, which allows you to develop new applications that will be portable and run FAST. Includes many useful vision routines, including camer
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robustly fits an affine fundamental matrix to a set of putatively matched image points-robustly fits an affine fundamental matri x to a set of putatively matched image points
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robustly fits a fundamental matrix to a set of putatively matched image points. This function uses an 8 point fundamental matrix solution-robustly fits a fundamental matrix to a set of putatively matched image points. This funct ion uses an eight poi
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robustly fits a fundamental matrix to a set of putatively matched image points.-robustly fits a fundamental matrix to a set of putatively matched image points.
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there are two parts in these codes. the first implements an eight point algorithm which is used to compute the fundamental matrix in computer vision. the second is used to compute the optical flow and the unreliable region.
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C++ code implementing the estimation of errors-in-variables models under point dependent noise. It includes examples for linear, ellipse, fundamental matrix and trifocal tensor estimation. The theory is described in A general method for errors-in-var
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计算基本矩阵的matlab例程，可供学习科研时参考,Calculation of the basic matrix matlab routines for scientific study and reference
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计算机视觉中得八点算法，采用SVD分解最小二乘解来求基本矩阵，这是模拟仿真实验程序。-Was 8:00 in computer vision algorithms, using SVD decomposition least-squares solution to seek the fundamental matrix, which is simulation, experimental procedure.
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利用RANSAC算法鲁棒性的计算两幅视图间的基本矩阵，本代码含有7点算法，8点算法-RANSAC algorithm using the calculation of robust fundamental matrix between two views, this code contains the algorithm 7, 8-point algorithm
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sift特征点的提取匹配后使用Ransac进行基本矩阵的估计-sift the extraction of feature points were matched using the fundamental matrix estimation Ransac
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利用Matlab和SPSS软件实现聚类分析.运用Matlab中的一些基本矩阵计算方法，通过自己编程实现聚类算法-Matlab and SPSS software using cluster analysis. The use of Matlab, some of the fundamental matrix method, clustering algorithms, through their own programming
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计算机视觉作业，实现两幅图片中的极线、极点计算和基础矩阵的求取。-Computer vision homework.It is to calculate the polar, pole and the fundamental matrix calculation between two image.
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这是一段改进的八点算法，用来求基本矩阵的，并且用matlab进行了实现-This is a modified eight algorithms used to find the fundamental matrix, and was realized with matlab
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计算机视觉中基本矩阵F估计的matlab程序，很有用-F fundamental matrix in computer vision estimates matlab program, very useful
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运用Matlab中的一些基本矩阵计算方法，通过自己编程实现聚类算法，在此只讨论根据最短距离规则聚类的方法。-The use of Matlab, some of the fundamental matrix method, clustering algorithms, through their own programming, in which only discuss the rules under the shortest distance clustering method.
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立体匹配，包括计算基本矩阵，极线校正，和SSD计算匹配点-Matching, including the calculation of fundamental matrix, epipolar correction, and SSD calculation of matching points
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根据计算机视觉的基本理论，通过摄像机自标定的方法得到基本矩阵F，再利用特征提取的方法将物体上的关键点映射到三维空间，并转换到欧式坐标系下，从而得到物体运动过程中的六自由度分量。-According to the basic theory of computer vision, through the camera self-calibration method to be the fundamental matrix F, re-use feature extraction methods on
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基于RANSAC算法的基础矩阵求解相机的参数-The fundamental matrix based on RANSAC algorithm to solve the camera parameters
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Projection Based M-Estimator ,一个基于M
-Estimator估计器的投影程序，能够很好的估计，计算机图像领域的线性、异方差（椭圆和 基础矩阵）和子空间等。- using the base class for linear, heteroscedastic (ellipse and fundamental matrix) and subspace estimation are included in the program.
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implement linear least square solution to estimating the fundamental matrix
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