| Re: [eigen] get scaling out of transform? |
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- To: eigen@xxxxxxxxxxxxxxxxxxx
- Subject: Re: [eigen] get scaling out of transform?
- From: Benoit Jacob <jacob.benoit.1@xxxxxxxxx>
- Date: Thu, 22 Jan 2009 19:23:53 +0100
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2009/1/22 Jitse Niesen <jitse@xxxxxxxxxxxxxxxxx>:
> On Wed, 21 Jan 2009, Benoit Jacob wrote:
>
>> There's another way that you can go, suffering again performance-wise
>> from the current lack of fixed-size specializations: use the
>> SelfAdjointEigenSolver.
>>
>> Transform3d t;
>> Matrix3d m = t.linear();
>> SelfAdjointEigenSolver s(m*m.adjoint());
>> Matrix3d scaling = s.operatorSqrt();
>
> This is numerically a bit dangerous. You lose information when computing the
> product m*m.adjoint(). This may not be that important in this case though,
> because the matrices are small and (I'd guess) the accuracy requirement is
> lax.
I agree. Indeed it wouldn't be a problem here because the matrices are small.
Anyway, the solution that i've used to implement
computeRotationScaling today is using the SVD, not the
SelfAdjointEigenSolver, so I don't need to form this matrix product.
Cheers,
Benoit
>
>
> Jitse
>
>
>