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Hi Maia
You could first calculate the posterior based on the landmarks and afterwards use the downsampling. Like this you do not have to care that the landmarks are still present in the downsampled version, but your registration can still be guided by them.
Best regards
Andreas
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If you have a new enough version of Scalismo a function is
already included in e.g. StatisticalMeshModel
/** * Changes the number of vertices on which the model is defined * @param targetNumberOfVertices The desired number of vertices * @return The new model */ def decimate(targetNumberOfVertices: Int): StatisticalMeshModel = { val newReference = referenceMesh.operations.decimate(targetNumberOfVertices) val interpolator = TriangleMeshInterpolator3D[EuclideanVector[_3D]]() val newGp = gp.interpolate(interpolator) StatisticalMeshModel(newReference, newGp) }
Best regards
Andreas
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