Authors: Dan Raviv Alexander M Bronstein Michael M Bronstein Ron Kimmel
Publish Date: 2010/02/12
Volume: 89, Issue: 1, Pages: 18-39
Abstract
Symmetry and selfsimilarity are the cornerstone of Nature exhibiting themselves through the shapes of natural creations and ubiquitous laws of physics Since many natural objects are symmetric the absence of symmetry can often be an indication of some anomaly or abnormal behavior Therefore detection of asymmetries is important in numerous practical applications including crystallography medical imaging and face recognition to mention a few Conversely the assumption of underlying shape symmetry can facilitate solutions to many problems in shape reconstruction and analysis Traditionally symmetries are described as extrinsic geometric properties of the shape While being adequate for rigid shapes such a description is inappropriate for nonrigid ones extrinsic symmetry can be broken as a result of shape deformations while its intrinsic symmetry is preserved In this paper we present a generalization of symmetries for nonrigid shapes and a numerical framework for their analysis addressing the problems of full and partial exact and approximate symmetry detection and classification
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