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Anisotropic Laplace-Beltrami eigenmaps: Bridging Reeb graphs and skeletons
Yonggang Shi   Rongjie Lai   Krishna, S.   Sicotte, N.   Dinov, I.   Toga, A.W.  
Lab. of Neuro Imaging, UCLA Sch. of Med., Los Angeles, CA;

This paper appears in: Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Publication Date: 23-28 June 2008
On page(s): 1-7
Location: Anchorage, AK,
ISBN: 978-1-4244-2339-2
INSPEC Accession Number: 10104363
Digital Object Identifier: 10.1109/CVPRW.2008.4563018
Current Version Published: 2008-07-15

Abstract
In this paper we propose a novel approach of computing skeletons of robust topology for simply connected surfaces with boundary by constructing Reeb graphs from the eigen-functions of an anisotropic Laplace-Beltrami operator. Our work brings together the idea of Reeb graphs and skeletons by incorporating a flux-based weight function into the Laplace-Beltrami operator. Based on the intrinsic geometry of the surface, the resulting Reeb graph is pose independent and captures the global profile of surface geometry. Our algorithm is very efficient and it only takes several seconds to compute on neuroanatomical structures such as the cingulate gyrus and corpus callosum. In our experiments, we show that the Reeb graphs serve well as an approximate skeleton with consistent topology while following the main body of conventional skeletons quite accurately.

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