文件列表:

RO算法 (0, 2012-03-08)
RO算法\Debug (0, 2012-03-08)
RO算法\Debug\LineParamEstimator.obj (56569, 2012-03-08)
RO算法\Debug\LineParamEstimator.sbr (0, 2012-03-08)
RO算法\Debug\Point2D.obj (1993, 2012-03-08)
RO算法\Debug\Point2D.sbr (0, 2012-03-08)
RO算法\Debug\RANSAC.bsc (394240, 2012-03-08)
RO算法\Debug\RANSAC.exe (241749, 2012-03-08)
RO算法\Debug\RANSAC.ilk (468192, 2012-03-08)
RO算法\Debug\RANSAC.pdb (623616, 2012-03-08)
RO算法\Debug\RansacExample.obj (62430, 2012-03-08)
RO算法\Debug\RansacExample.sbr (0, 2012-03-08)
RO算法\Debug\vc60.idb (91136, 2012-03-08)
RO算法\Debug\vc60.pdb (102400, 2012-03-08)
RO算法\LineParamEstimator.cpp (4653, 2004-05-11)
RO算法\LineParamEstimator.h (2693, 2004-05-12)
RO算法\ParameterEsitmator.h (1765, 2004-05-12)
RO算法\Point2D.cpp (22, 2004-05-11)
RO算法\Point2D.h (442, 2004-05-12)
RO算法\RANSAC.dsp (4729, 2012-03-07)
RO算法\RANSAC.dsw (535, 2004-05-11)
RO算法\RANSAC.ncb (91136, 2012-03-08)
RO算法\RANSAC.opt (54784, 2012-03-08)
RO算法\RANSAC.plg (246, 2012-03-08)
RO算法\Ransac.h (13096, 2004-05-12)
RO算法\RansacExample.cpp (4004, 2012-03-08)
RO算法\Unix_Makefile (286, 2004-05-12)

Author: Ziv Yaniv (zivy@cs.huji.ac.il) This archive contains an implementation of the Random Sample Consensus (Ransac) framework for robust parameter estimation. The archive includes the following files: 1. Project files for VC++ 6.0. 2. A Unix Makefile. 3. Source files: Point2D.{cpp,h} - Primitive 2D point class used in the example. ParameterEstimator.h - A virtual class, the ancestor of all parameter estimators. LineParamEstimator.{cpp,h} - Class which implements the virtual functions defined by the ParameterEstimator class, for 2D lines. Ransac.h - Template implementation of the Ransac algorithm. RansacExample.cpp - An example which shows how to use the Ransac template. Notes: 1. The math underlying the code which performs a least squares fit for the line is described in the summary on Principle Component Analysis (PCA) found on my web site (look under lesson handouts). Read the orthogonal least squares section and the section about eigenvectors/eigenvalues of symmetric 2X2 matrices. 2. For a detailed description of the Ransac see: * Martin A. Fischler, Robert C. Bolles, ``Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography'', Communications of the ACM, Vol. 24(6), 1***1. **Richard I. Hartely, Andrew Zisserman, "Multiple View Geometry in Computer Vision", Cambridge University Press, 2000. 3. This template implementation has been successfully used to estimate the parameters of: a. lines b. circles c. ellipses d. homographies I only provide the line parameter estimator as it is the only estimator that does not require the availability of linear algebra packages or non-linear optimization code.

近期下载者：

相关文件：

评论：[我要评论] [举报此文件]

收藏者：