[ITK-users] How can I calculate PCA Principal Modes means?

[Viki MCG]

I'm using itk::GeodesicActiveContourShapePriorLevelSetImageFilter. I read
the example given in (
http://www.itk.org/Doxygen/html/Examples_2Segmentation_2GeodesicActiveContourShapePriorLevelSetImageFilter_8cxx-example.html)
but I don't understand the following paragraph.

// The parameters of the distribution are user-specified. Since we
// assumed the principal modes have already been normalized,
// we set the distribution to zero mean and unit variance.
CostFunctionType::ArrayType mean( shape->GetNumberOfShapeParameters() );
CostFunctionType::ArrayType stddev( shape->GetNumberOfShapeParameters() );
mean.Fill( 0.0 );
stddev.Fill( 1.0 );
costFunction->SetShapeParameterMeans( mean );
costFunction->SetShapeParameterStandardDeviations( stddev );

Supposing that I have NOT normalized the principal modes, how can I
calculate their means? I got principal modes using
itk::ImagePCAShapeModelEstimator and I know their standard deviations are
sqrt(eigen values), but I don't see how can I know their means.

Any help would be very appreciated.

Thanks in advance,

Viki.
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