Our goal is to develop a smoothing algorithm, which would be feature preserving and simple to use without the need of extensive parameter tuning. Our method does the smoothing of vertices based on local neighbourhood character, which is modeled by a covariance matrix of neighbourhood triangle normals. The eigenvalues and eigenvectors of the covariance matrix are used for local weighting of the displacement vector of laplacian operator. This way the method is locally auto-tuned.

Our goal is to develop a smoothing algorithm, which would be feature preserving and simple to use without the need of extensive parameter tuning. Our method does the smoothing of vertices based on local neighbourhood character, which is modeled by a covariance matrix of neighbourhood triangle normals. The eigenvalues and eigenvectors of the covariance matrix are used for local weighting of the displacement vector of laplacian operator. This way the method is locally auto-tuned.