请教各位大神关于ICP（迭代最近点算法）的问题
目前所知的ICP代码都是把两个模型的所有数据传入，计算旋转矩阵和平移向量，然后对前后模型进行匹配。如果已知三对初始对应点，该怎么改代码实现通过这三对初始对应点使前后模型匹配？代码如下function = icp2(data1, data2, res, tri)
% = icp2(data1, data2, res, tri)
%
% This is an implementation of the Iterative Closest Point (ICP) algorithm.
% The function takes two data sets and registers data2 with data1. It is
% assumed that data1 and data2 are in approximation registration. The code
% iterates till no more correspondences can be found.
%
% This is a modified version (12 April, 2005). It is more accurate and has
% less chances of getting stuck in a local minimum as opposed to my earlier
% version icp.m
%
% Arguments: data1 - 3 x n matrix of the x, y and z coordinates of data set 1
% data2 - 3 x m matrix of the x, y and z coordinates of data set 2
% res - the tolerance distance for establishing closest point
% correspondences. Normally set equal to the resolution
% of data1
% tri - optional argument. obtained by tri = delaunayn(data1');
%
% Returns: R - 3 x 3 accumulative rotation matrix used to register data2
% t - 3 x 1 accumulative translation vector used to register data2
% corr - p x 3 matrix of the index no.s of the corresponding points of
% data1 and data2 and their corresponding Euclidean distance
% error - the mean error between the corresponding points of data1
% and data2 (normalized with res)
% data2 - 3 x m matrix of the registered data2
%
figure(1),plot3(data1(1,:),data1(2,:),data1(3,:),'r.',data2(1,:),data2(2,:),data2(3,:),'c.'),hold off;
maxIter = 30;
c1 = 0;
c2 = 1;
R = eye(3);
t = zeros(3,1);
if nargin < 4
tri = delaunayn(data1');
end
n = 0;
while c2 ~= c1
c1 = c2;
= dsearchn(data1', tri, data2');
corr(:,2:3) = [' D];
corr(find(D>2*res),:) = [];%去除异常点
corr = -sortrows(-corr,3);
corr = sortrows(corr,1);
= unique(corr(:,1));
corr = corr(Bi,:);
= reg(data1, data2, corr);
data2 = R1*data2;
data2 = ;
R = R1*R;
t = R1*t + t1;
c2 = length(corr);
n = n + 1;
if n > maxIter
break;
end
end
e1 = 1000001;
e2 = 1000000;
n = 0;
noChangeCount = 0;
while noChangeCount < 10
e1 = e2;
= dsearchn(data1', tri, data2');
corr(:,2:3) = [' D];
corr(find(D>2*res),:) = [];
corr = -sortrows(-corr,3);
corr = sortrows(corr,1);
= unique(corr(:,1));
corr = corr(Bi,:);
= reg(data1, data2, corr);
data2 = R1*data2;
data2 = ;
R = R1*R;
t = R1*t + t1;
e2 = sum(corr(:,3))/(length(corr)*res);
n = n + 1;
if n > maxIter
break;
end
if abs(e2-e1)<res/10000
noChangeCount = noChangeCount + 1;
end
end
error = min(e1,e2);
figure(2),plot3(data1(1,:),data1(2,:),data1(3,:),'r.',data2(1,:),data2(2,:),data2(3,:),'b.'),hold off;%新加的
%-----------------------------------------------------------------
function = reg(data1, data2, corr)
n = length(corr);
M = data1(:,corr(:,1));
mm = mean(M,2);
S = data2(:,corr(:,2));
ms = mean(S,2);
Sshifted = ;
Mshifted = ;
K = Sshifted*Mshifted';
K = K/n;
= svd(K);
R1 = V*U';
if det(R1)<0
B = eye(3);
B(3,3) = det(V*U');
R1 = V*B*U';
end
t1 = mm - R1*ms;
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