# noisy_target_alignment_transform¶

menpofit.fitter.noisy_target_alignment_transform(source, target, alignment_transform_cls=<class 'menpo.transform.homogeneous.affine.AlignmentAffine'>, noise_std=0.1, **kwargs)[source]

Constructs the optimal alignment transform between the source and a noisy version of the target obtained by adding white noise to each of its points.

Parameters
• source (menpo.shape.PointCloud) – The source pointcloud instance used in the alignment

• target (menpo.shape.PointCloud) – The target pointcloud instance used in the alignment

• alignment_transform_cls (menpo.transform.Alignment, optional) – The alignment transform class used to perform the alignment.

• noise_std (float or list of float, optional) – The standard deviation of the white noise to be added to each one of the target points. If float, then the same standard deviation is used for all points. If list, then it must define a value per point.

Returns

noisy_transform (menpo.transform.Alignment) – The noisy Similarity Transform