资源简介
一个简单的随机抽样一致性算法(matlab)
代码片段和文件信息
function [results options] = RANSAC(X options)
% [results options] = RANSAC(X options)
%
% DESC:
% estimate the vector of parameters Theta using RANSAC (see source [1]
% [2])
%
% VERSION:
% 1.1.5
%
% INPUT:
%
% X = input data. The data id provided as a matrix that has
% dimesnsions 2dxN where d is the data dimensionality
% and N is the number of elements
%
% options = structure containing the following fields:
%
% sigma = noise std
% P_inlier = Chi squared probability threshold for inliers
% (i.e. the probability that an point whose squared
% error is less than T_noise_squared is an inlier)
% (default = 0.99)
% T_noise_squared = Error threshold (overrides sigma)
% epsilon = False Alarm Rate (i.e. the probability we never
% pick a good minimal sample set) (default = 1e-3)
% Ps = sampling probability ( 1 x size(X 2) )
% (default: uniform i.e. Ps is empty)
% ind_tabu = logical array indicating the elements that should
% not be considered to construct the MSS (default
% is empty)
% validateMSS_fun = function that validates a MSS
% Should be in the form of:
%
% flag = validateMSS_foo(X s)
%
% validateTheta_fun = function that validates a parameter vector
% Should be in the form of:
%
% flag = validateTheta_foo(X Theta s)
%
% est_fun = function that estimates Theta.
% Should be in the form of:
%
% [Theta k] = estimate_foo(X s)
%
% man_fun = function that returns the residual error.
% Should be in the form of:
%
% [E T_noise_squared] = man_fun(Theta X)
%
% mode = algorithm flavour
% ‘RANSAC‘ -> Fischler & Bolles
% ‘MSAC‘ -> Torr & Zisserman
%
%
% max_iters = maximum number of iterations (default = inf)
% min_iters = minimum number of iterations (default = 0)
% max_no_updates = maximum number of iterations with no updates
% (default = inf)
% fix_seed = true to fix the seed of the random number
% generator so that the results on the same data
% set are repeatable (default = false)
% reestimate = true to resestimate the parameter vector using
% all the detected inliers
% (default = false)
% verbose = true for verbose output
% (default = true)
% notify_iters = if verbose output is on then print some
%
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 1378 2008-11-27 01:15 RANSAC\Common\chi2inv_LUT.m
文件 33667 2008-11-19 23:54 RANSAC\Common\chi2inv_LUT.mat
文件 635 2008-11-27 01:15 RANSAC\Common\chi2inv_mathworks\generate_chi2inv_LUT.m
文件 1144 2008-11-27 01:15 RANSAC\Common\get_consensus_set.m
文件 1591 2008-11-27 01:15 RANSAC\Common\get_consensus_set_cost.m
文件 657 2008-11-27 01:15 RANSAC\Common\get_iter_RANSAC.m
文件 2939 2008-11-27 01:15 RANSAC\Common\get_minimal_sample_set.m
文件 799 2008-11-27 01:15 RANSAC\Common\get_q_RANSAC.m
文件 1092 2008-11-27 01:15 RANSAC\Common\get_rand.m
文件 1888 2008-11-27 01:15 RANSAC\Common\get_rand_prob.m
文件 5345 2008-11-27 01:15 RANSAC\Common\stabilize.m
文件 7639 2008-11-19 23:54 RANSAC\COPYING.LESSER.txt
文件 35147 2008-11-19 23:54 RANSAC\COPYING.txt
文件 890197 2008-11-27 01:03 RANSAC\Docs\RANSAC4Dummies.pdf
文件 6148 2008-11-25 17:10 RANSAC\Examples\.DS_Store
文件 18087 2008-11-19 23:54 RANSAC\Examples\LineData.mat
文件 2039 2008-11-27 01:15 RANSAC\Examples\test_RANSAC_homography.m
文件 2389 2008-11-27 01:15 RANSAC\Examples\test_RANSAC_line_01.m
文件 1502 2008-11-27 01:15 RANSAC\Examples\test_RANSAC_line_02.m
文件 2638 2008-11-27 01:15 RANSAC\Examples\test_RANSAC_plane.m
文件 2086 2008-11-27 01:15 RANSAC\Examples\test_RANSAC_RST.m
文件 11 2008-11-25 17:34 RANSAC\Examples\VERSION.txt
文件 848 2008-11-27 01:15 RANSAC\Models\Common\cart2homo.m
文件 749 2008-11-27 01:15 RANSAC\Models\Common\homo2cart.m
文件 1119 2008-11-27 01:15 RANSAC\Models\Common\normalize_points.m
文件 1687 2008-11-27 01:15 RANSAC\Models\error_foo.m
文件 1453 2008-11-27 01:15 RANSAC\Models\estimate_foo.m
文件 1726 2008-11-27 01:15 RANSAC\Models\Homography\error_homography.m
文件 1308 2008-11-27 01:15 RANSAC\Models\Homography\estimate_homography.m
文件 3461 2008-11-27 01:15 RANSAC\Models\Homography\HomographyDLT.m
............此处省略31个文件信息
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