Robust Rigid Shape Registration Method Using a Level Set Formulation
Robust Rigid Shape Registration Method Using a Level Set Formulation
This paper presents a fast algorithm for robust registration of shapes implicitly represented by signed distance functions(SDF). The proposed algorithm aims to recover the transformation parameters( scaling, rotation, and translation) by minimizing the dissimilarity between two shapes. To achieve a robust and fast algorithm, linear orthogonal transformations are employed to minimize the dissimilarity measures. The algorithm is applied to various shape registration problems, to address issues such as topological invariance, shape complexity, and convergence speed and stability. The outcomes are compared with other state-of-the-art shape registration algorithms to show the advantages of the new technique.
252-261
Al-Huseiny, Muayed
89bace65-62ba-4531-a4c2-bae3f1dd0c0f
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
November 2010
Al-Huseiny, Muayed
89bace65-62ba-4531-a4c2-bae3f1dd0c0f
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Al-Huseiny, Muayed, Mahmoodi, Sasan and Nixon, Mark
(2010)
Robust Rigid Shape Registration Method Using a Level Set Formulation.
Lecture Notes in Computer Science-6th International Symposium on Visual Computing, Las Vegas, United States.
.
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Abstract
This paper presents a fast algorithm for robust registration of shapes implicitly represented by signed distance functions(SDF). The proposed algorithm aims to recover the transformation parameters( scaling, rotation, and translation) by minimizing the dissimilarity between two shapes. To achieve a robust and fast algorithm, linear orthogonal transformations are employed to minimize the dissimilarity measures. The algorithm is applied to various shape registration problems, to address issues such as topological invariance, shape complexity, and convergence speed and stability. The outcomes are compared with other state-of-the-art shape registration algorithms to show the advantages of the new technique.
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ISVC2010Registration.pdf
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Published date: November 2010
Additional Information:
Event Dates: Novemeber 2010
Venue - Dates:
Lecture Notes in Computer Science-6th International Symposium on Visual Computing, Las Vegas, United States, 2010-11-01
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 271517
URI: http://eprints.soton.ac.uk/id/eprint/271517
PURE UUID: ebe716fb-4690-420b-9649-bd5957b730ca
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Date deposited: 06 Sep 2010 15:27
Last modified: 15 Mar 2024 02:35
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Contributors
Author:
Muayed Al-Huseiny
Author:
Sasan Mahmoodi
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