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Robust Rigid Shape Registration Method Using a Level Set Formulation

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
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, United States. pp. 252-261 .

Record type: Conference or Workshop Item (Other)

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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More information

Published date: November 2010
Additional Information: Event Dates: Novemeber 2010
Venue - Dates: Lecture Notes in Computer Science-6th International Symposium on Visual Computing, United States, 2010-11-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 271517
URI: https://eprints.soton.ac.uk/id/eprint/271517
PURE UUID: ebe716fb-4690-420b-9649-bd5957b730ca
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 06 Sep 2010 15:27
Last modified: 06 Jun 2018 13:18

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