I would like to calculate the best fit plane with the svd class in opencv. But I do not know how to use it. I have a vector of point3f. What is the correction way to us SVD class. My problem is mainly do not know how to pass the correct parameter into the function. Would anyone provide me a sample code so that I can follow?
My data are 9 points (0,0,1) (1,0,3) (2,0,5) (0,1,4) , (1,1,8) (2,1,7) (0,2,7) (1,2,8) (2,2,8)
I want to solve z = M p where p=[ a b c] and a xi+ byi +c =zi
Mat z=(Mat_<double>(9,1) << 1, 3, 5, 4, 8, 7, 7, 8, 8);
Mat m=(Mat_<double>(9,3) << 0, 0 ,1/**/,1,0 ,1/**/,2 ,0 ,1/**/,0 ,1 ,1/**/,1 ,1, 1/**/, 2, 1, 1/**/, 0,2, 1/**/, 1,2,1/**/, 2, 2, 1);
SVD s(m);
Mat dst;
Mat singularValue;
s.backSubst(z,dst);
cout<<"Solution z= m dst"<< dst<<endl;
s.compute(m,singularValue);
cout<<"singular value :"<<singularValue<<endl;
Mat mp=(Mat_<double>(9,4) << 0, 0 ,1,1/**/,1,0 ,3,1/**/,2 ,0 ,5,1/**/,0 ,1 ,4,1/**/,1 ,1, 8,1/**/,2, 1, 7,1/**/, 0, 2, 7,1/**/, 1,2,8,1/**/, 2, 2, 8,1);
SVD s2(mp);
Mat a;
s2.solveZ(mp,a);
cout<<"Solution mp *a =0"<<a<<endl;
and it gives answer :
Solution z= m dst[1.333333333333331;
2.333333333333332;
2.000000000000002]
singular value :[5.592252381884617;
2.449489742783178;
1.314044632919994]
Solution mp *a =0[0.3330915074747192;
0.6439188217126393;
-0.2753503146060172;
0.6313484005989033]
I hope it will help you
Thank you very much. I have an additional question. What is the difference betweeen backSubst and the direct SVD calculation?(link: http://docs.opencv.org/master/df/df7/... last two public member functions
Asked: 2015-11-30 09:41:54 -0600
Seen: 1,146 times
Last updated: Dec 01 '15
