find_good_sample.m~

一个用EM算法的源程序

function positiveSample = find_good_sample(X, normals)

% Basic criteria for picking a good representive sample:
% 1. X coordinates far away from the origin
% 2. Its normal vector must not be short, which will be influenced more by
% the noise

[ambientDimension sampleNumber]= size(X);

for sampleIndex=1:sampleNumber
    xNorm(sampleIndex)=norm(X(:,sampleIndex));
end

[ignored, index] = sort(xNorm,'descend');

preserveIndex = ceil(sampleNumber/2);
normalNorm=zeros(1, preserveIndex);
for sampleIndex = 1: preserveIndex
    normalNorm(sampleIndex)=norm(normals(:,index(sampleIndex)));
end

[ignored,normalIndex] = sort(normalNorm,'descend');

% Randomly pick one sample in