[Insight-users] Lidar-toImage registration with Rigid3DPerspectiveTransform

[Luis Ibanez]

Hi Ruisheng,

Unfortunately we don't have specific examples for this
configuration of registration (Lidar-to-Image) in the
ITK source tree.

However,

You may find useful to look at the code of the test:

   Insight/Testing/Code/Algorithms/
         itkPointSetToImageRegistrationTest_1.cxx


   Regards,


          Luis


-----------------------------------------------------------------------------
On Mon, Apr 12, 2010 at 3:26 PM, ruisheng wang <ruisheng at cim.mcgill.ca>wrote:

> Hi Luis,
>
> Thank you very much for your replies. Do you have an example code showing
> the process of Lidar-to-Image registration using
> Mutual informaiton. I could not find examples for doing this. In the ITK
> document, there is not an example showing
> PointSetToimageRegistration, do you have an example code showing how to use
> PointSetToImageregistration?
>
> thanks a lot!
> Ruisheng
> \
>
>
>
> On Sat, Apr 3, 2010 at 5:33 PM, Luis Ibanez <luis.ibanez at kitware.com>wrote:
>
>> Hi Ruisheng,
>>
>> In order to use this class effectively, you should
>> first become very familiar with the ITK Registration
>> Framework.
>>
>> Please read the ITK Software Guide:
>>
>>       http://www.itk.org/ItkSoftwareGuide.pdf
>>
>> In particular the Chapter 8 "Image Registration"
>> in pdf-pages:  347-533.
>>
>>
>> Once you are familiar with the framework,
>> you may want use the following configuration:
>>
>>
>> 1) Use the PointSetToImageRegistration class
>>
>> 2) Use the itkPointSetToImageMetric class
>>
>> 3) Use the perspective transform
>>
>> 4) Start with an optimizer that does not require
>>    derivatives (e.g. the Amoeba optimizer).
>>
>>
>> Key factors for a successful registration are:
>>
>> A)  Good initialization of the Transform
>>
>> B)  Steady setup for the optimizer parameters
>>
>> C) Proper scaling of the Transform parameters.
>>
>> In your case, please note that (A) includes to
>> make a very good initialization for the center
>> of projection and the focal distance, and that
>> (B) means that you should start with optimizer
>> settings that barely modify the Transform, and
>> from them you can progress towards having
>> the Transform explore a wider range of
>> parameters.
>>
>>
>>      Regards,
>>
>>
>>             Luis
>>
>>
>> -----------------------------------------------------------------------
>> On Fri, Apr 2, 2010 at 3:11 PM, ruisheng wang <ruisheng at cim.mcgill.ca>
>> wrote:
>> > Hi everyone,
>> >
>> > I'm trying to register 3D lidar with 2D optical images using the
>> transform
>> > ITK::Rigid3DPerspectiveTransform.
>> > But seems there is not much explanation or examples from ITK to describe
>> the
>> > this functions. I wonder if
>> > anyone here could give me some hints for how to use
>> > ITK::Rigid3DPerspectiveTransform for the 3D-to2D registration
>> > problems.
>> >
>> > Thanks very much!
>> > Ruisheng
>> >
>> >
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