TY - JOUR
T1 - Full and partial symmetries of non-rigid shapes
AU - Raviv, Dan
AU - Bronstein, Alexander M.
AU - Bronstein, Michael M.
AU - Kimmel, Ron
N1 - Funding Information:
Fig. 23 Low partiality coefficient (left) versus a high one (right) in the Pareto frontier. The symmetric surface is colored red. See color version online Fig. 24 Low regularization coefficient (left) versus a high one (right) in the Pareto frontier. The symmetric surface is colored red. See color version online Fig. 25 Ambiguity of partial symmetries: a shape with an asymmetric deformation can be interpreted in two ways: as a shape having an approximate full symmetry (left) or as a shape having an exact partial symmetry (right). Both interpretations correspond to Pareto-optimal choices of ε and λ Acknowledgements This research was supported in part by the Israel Science Foundation (grant no. ISF 623/08), by The United States-Israel Bi-national Science Foundation (grant no. BSF 2004274), the USA Office of Naval Research (ONR), and by the New York metropolitan research fund.
PY - 2010/8
Y1 - 2010/8
N2 - Symmetry and self-similarity 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 non-rigid 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 non-rigid shapes and a numerical framework for their analysis, addressing the problems of full and partial exact and approximate symmetry detection and classification.
AB - Symmetry and self-similarity 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 non-rigid 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 non-rigid shapes and a numerical framework for their analysis, addressing the problems of full and partial exact and approximate symmetry detection and classification.
KW - Intrinsic
KW - Non-rigid
KW - Partiality
KW - Self-similarity
KW - Symmetry
UR - http://www.scopus.com/inward/record.url?scp=77951295679&partnerID=8YFLogxK
U2 - 10.1007/s11263-010-0320-3
DO - 10.1007/s11263-010-0320-3
M3 - מאמר
AN - SCOPUS:77951295679
VL - 89
SP - 18
EP - 39
JO - International Journal of Computer Vision
JF - International Journal of Computer Vision
SN - 0920-5691
IS - 1
ER -