📄 ransacfitline.m
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% RANSACFITLINE - fits line to 3D array of points using RANSAC%% Usage [L, inliers] = ransacfitline(XYZ, t, feedback)%% This function uses the RANSAC algorithm to robustly fit a line% to a set of 3D data points.%% Arguments:% XYZ - 3xNpts array of xyz coordinates to fit line to.% t - The distance threshold between data point and the line% used to decide whether a point is an inlier or not.% feedback - Optional flag 0 or 1 to turn on RANSAC feedback% information.%% Returns:.% V - Line obtained by a simple fitting on the points that% are considered inliers. The line goes through the% calculated mean of the inlier points, and is parallel to% the principal eigenvector. The line is scaled by the% square root of the largest eigenvalue.% This line is a n*2 matrix. The first column is the% beginning point, the second column is the end point of the% line.% L - The two points in the data set that were found to% define a line having the most number of inliers.% The two columns of L defining the two points.% inliers - The indices of the points that were considered% inliers to the fitted line.%% See also: RANSAC, FITPLANE, RANSACFITPLANE% Copyright (c) 2003-2006 Peter Kovesi and Felix Duvallet (CMU)% School of Computer Science & Software Engineering% The University of Western Australia% http://www.csse.uwa.edu.au/% % Permission is hereby granted, free of charge, to any person obtaining a copy% of this software and associated documentation files (the "Software"), to deal% in the Software without restriction, subject to the following conditions:% % The above copyright notice and this permission notice shall be included in % all copies or substantial portions of the Software.%% The Software is provided "as is", without warranty of any kind.% Aug 2006 - created ransacfitline from ransacfitplane% author: Felix Duvalletfunction [V, L, inliers] = ransacfitline(XYZ, t, feedback) if nargin == 2 feedback = 0; end [rows, npts] = size(XYZ); if rows ~=3 error('data is not 3D'); end if npts < 2 error('too few points to fit line'); end s = 2; % Minimum No of points needed to fit a line. fittingfn = @defineline; distfn = @lineptdist; degenfn = @isdegenerate; [L, inliers] = ransac(XYZ, fittingfn, distfn, degenfn, s, t, feedback); % Find the line going through the mean, parallel to the major % eigenvector V = fitline3d(XYZ(:, inliers)); %------------------------------------------------------------------------% Function to define a line given 2 data points as required by% RANSAC.function L = defineline(X); L = X; %------------------------------------------------------------------------% Function to calculate distances between a line and a an array of points.% The line is defined by a 3x2 matrix, L. The two columns of L defining% two points that are the endpoints of the line.%% A line can be defined with two points as:% lambda*p1 + (1-lambda)*p2% Then, the distance between the line and another point (p3) is:% norm( lambda*p1 + (1-lambda)*p2 - p3 )% where% (p2-p1).(p2-p3)% lambda = ---------------% (p1-p2).(p1-p2)%% lambda can be found by taking the derivative of:% (lambda*p1 + (1-lambda)*p2 - p3)*(lambda*p1 + (1-lambda)*p2 - p3)% with respect to lambda and setting it equal to zerofunction [inliers, L] = lineptdist(L, X, t) p1 = L(:,1); p2 = L(:,2); npts = length(X); d = zeros(npts, 1); for i = 1:npts p3 = X(:,i); lambda = dot((p2 - p1), (p2-p3)) / dot( (p1-p2), (p1-p2) ); d(i) = norm(lambda*p1 + (1-lambda)*p2 - p3); end inliers = find(abs(d) < t); %------------------------------------------------------------------------% Function to determine whether a set of 2 points are in a degenerate% configuration for fitting a line as required by RANSAC.% In this case two points are degenerate if they are the same point% or if they are exceedingly close together.function r = isdegenerate(X) %find the norm of the difference of the two points % this will be 0 iff the two points are the same (the norm of their % difference is zero) r = norm(X(:,1) - X(:,2)) < eps;
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