[Insight-users] Best optimizer for landmark registration with only 3 points

[Charlotte Curtis]

Thanks for the suggestion, Alireza.  I actually tried the
LandmarkBasedTransformInitializer, and the result wasn't very good, which
kind of surprised me as it seems that with the same landmarks it should
converge on approximately the same solution as the iterative closest point
method.  I do have correspondence between the points - does the
TransformInitializer not use the correspondence?  That could explain the
difference in the two solutions.

Thanks for your help,

Charlotte

On Dec 1, 2007 6:34 PM, Alireza Salamy <alireza_sal2000 at yahoo.com> wrote:

> Hi Charlotte
>
> If you only have Three points, you could rather use the class:
>
>          itkLandmarkBasedTransformInitializer
>
>
> if you do not have the correspondence between the points, well...
> this methods is so fast with only Three points that you could
> actually try all the combinations and settle for the one with
> the smallest final squared errors,otherwise your own suggestion of
> duplicating the landmarks should work.
>
> I hope it works.
> Alireza
>
>
> *Charlotte Curtis <curtisc at uoguelph.ca>* wrote:
>
> I'd like to use landmark registration to get a rough first guess prior to
> image registration.  When I run IterativeClosestPoint2 with 4 landmarks, it
> complains about the number of landmarks:
>
> vnl_least_squares_function: WARNING: unknowns(6) > residuals(4)
> vnl_levenberg_marquardt: Number of unknowns(6) greater than number of data
> (4)
> Solution = [0, 0, 0, 0, 0, 0]
>
> I'm just wondering if there's an optimizer that would let me get away with
> a minimum of three landmarks.  Since 3 points would define a unique location
> in 3D space, it seems to me that there shouldn't need to be 6.  Indeed, if I
> simply duplicate all of my landmarks and fool it into thinking it has 8
> unique points, it comes up with a reasonable solution.  This is my backup
> plan if nothing else works, but it seems a little messy.  Any suggestions?
> Thanks,
>
> Charlotte _______________________________________________
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>
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