@inproceedings{86fbb8f54463458c88617c1d6f631f0e,
title = "Anisotropic laplace-beltrami operators for shape analysis",
abstract = "This paper introduces an anisotropic Laplace-Beltrami operator for shape analysis. While keeping useful properties of the standard Laplace-Beltrami operator, it introduces variability in the directions of principal curvature, giving rise to a more intuitive and semantically meaningful diffusion process. Although the benefits of anisotropic diffusion have already been noted in the area of mesh processing (e.g. surface regularization), focusing on the Laplacian itself, rather than on the diffusion process it induces, opens the possibility to effectively replace the omnipresent Laplace-Beltrami operator in many shape analysis methods. After providing a mathematical formulation and analysis of this new operator, we derive a practical implementation on discrete meshes. Further, we demonstrate the effectiveness of our new operator when employed in conjunction with different methods for shape segmentation and matching.",
keywords = "Anisotropic diffusion, Curvature, Laplace-Beltrami operator, Non-rigid matching, Segmentation, Shape analysis",
author = "Mathieu Andreux and Emanuele Rodol{\'a} and Mathieu Aubry and Daniel Cremers",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 13th European Conference on Computer Vision, ECCV 2014 ; Conference date: 06-09-2014 Through 12-09-2014",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-16220-1\_21",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "299--312",
editor = "Lourdes Agapito and Bronstein, \{Michael M.\} and Carsten Rother",
booktitle = "Computer Vision - ECCV 2014 Workshops, Proceedings",
}