[Insight-users] point cloud registration

[Luis Ibanez]

Hi Dennis,

Performing non-homogeneous scaling and rotations
is equivalent to performing shearing. Therefore
once you consider having non-homogeneous scaling
you can equally well go for a full Affine transform.


You are right, the Similarity3DTransform was added
to ITK after release 2.0.1.  If you decide to use
this transform you may have to download the CVS
version of ITK.  Note that we anticipate to release
ITK 2.2 by August 31st.


If you want to insist in using non-homogeneous scaling
then you probably want to look at the transform:

ScaleSkewVersor3DTransform
http://www.itk.org/Insight/Doxygen/html/classitk_1_1ScaleSkewVersor3DTransform.html



   Regards,


     Luis



--------------------
Dennis Wenzel wrote:
> Hello Luis,
> 
>> You haven't quite read the full Registration Chapter.
>>
>>
>> It seems that you missed the
>>
>>            itk::Similarity3DTransform
>>
>> that is described in section 8.8.14, pdf-page 428,
>> along with the 2D example of its use in section
>> 8.6.3, pdf-page 387.
>>
>> A Similarity Transform performs rotation, translation
>> and scaling without any shearing.
>>
>>
>> You may find useful to read the entire Registration
>> chapter.
>>
> 
> I respectfully beg to differ -- I am pretty sure that I DID read the 
> entire chapter.
> 
> The Similarity3DTransform only handles *uniform* (homogeneous) scaling 
> with seven parameters.  As I mentioned, I need 9 parameters which allows 
> me to have *non-uniform* (non-homogeneous) scaling.
> 
> Furthermore, I am using version 2.0.1 of ITK and there is no source for 
> itk::Similarity3DTransform -- only for itk::Similarity2DTransform.
> 
>>
>> The Euclidean distance metric will work regardless
>> of the Transform that you choose because the metric
>> is computed after the points have been transformed,
>> so it is always a measure of the residual error after
>> transformation.
>>
> 
> Dennis
> 
>