@Tomasz: Thanks for your comment! I have updated the function with your modification. I agree with you that this is a good way to ensure a plausible rotation matrix!
@Mark Brophy:
Thank you very much for pointing this out. I discovered that the kNearestNeighbors was missing altogether, and that kNN searching is supported only in Stat. Toolbox v. 7.5 or higher.
I added the missing sub function and updated the code, which should be available in about 24 hours.
@Pietro Pala:
I think you might be mistaking accuracy for robustness.
You are basically trying to register planes, and there is very little chance of converging with your data.
Try:
z(x,y) = 50*exp(-(x-25.0).^2 ./400.0 -(y-25.0).^2 ./400.0);
@Jaden:
I believe that everything in the algorithm is deterministic. However, I do not know the details of Mathwork's kD-tree implementation, and there might be some fuzziness.
You are not showing the code you run, so I have no chance to tell what exactly is going wrong.
Same results with 'Matching' == 'bruteForce' ?
Only works for simulated data. Real data needs a super high overlap already. Method works not as it should, it is more like iterative-most-overlap algorithm instead of closes point.
It seems working but only if the model and data are similar. I have an object AB (3D) composed of A and B. I am using AB as a model and A as data, but in this case A becomes twice bigger in order to fit AB ???
It seems working but only if the model and data are similar. I have an object AB (3D) composed of A and B. I am using AB as a model and A as data, but in this case A becomes twice bigger in order to fit AB ???
Only works for simulated data. Real data needs a super high overlap already. Method works not as it should, it is more like iterative-most-overlap algorithm instead of closes point.
1
10 Dec 2012
Iterative Closest Point
An implementation of various ICP (iterative closest point) features.
It seems working but only if the model and data are similar. I have an object AB (3D) composed of A and B. I am using AB as a model and A as data, but in this case A becomes twice bigger in order to fit AB ???
3
23 Nov 2012
Iterative Closest Point
An implementation of various ICP (iterative closest point) features.
It seems working but only if the model and data are similar. I have an object AB (3D) composed of A and B. I am using AB as a model and A as data, but in this case A becomes twice bigger in order to fit AB ???
Comment only