Surface Area Distribution Descriptor for object matching

Matching 3D objects by their similarity is a fundamental problem in computer vision, computer graphics and many other fields. The main challenge in object matching is to find a suitable shape representation that can be used to accurately and quickly discriminate between similar and dissimilar shapes...

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Main Authors: Mohamed F. Gafar, Elsayed E. Hemayed
Format: Article
Language:English
Published: Elsevier 2010-07-01
Series:Journal of Advanced Research
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2090123210000718
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author Mohamed F. Gafar
Elsayed E. Hemayed
author_facet Mohamed F. Gafar
Elsayed E. Hemayed
author_sort Mohamed F. Gafar
collection DOAJ
description Matching 3D objects by their similarity is a fundamental problem in computer vision, computer graphics and many other fields. The main challenge in object matching is to find a suitable shape representation that can be used to accurately and quickly discriminate between similar and dissimilar shapes. In this paper we present a new volumetric descriptor to represent 3D objects. The proposed descriptor is used to match objects under rigid transformations including uniform scaling. The descriptor represents the object by dividing it into shells, acquiring the area distribution of the object through those shells. The computed areas are normalised to make the descriptor scale-invariant in addition to rotation and translation invariant. The effectiveness and stability of the proposed descriptor to noise and variant sampling density as well as the effectiveness of the similarity measures are analysed and demonstrated through experimental results.
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spelling doaj.art-367885ca13f741e0873c677737bf41852022-12-21T20:00:47ZengElsevierJournal of Advanced Research2090-12322090-12242010-07-011323324110.1016/j.jare.2010.06.005Surface Area Distribution Descriptor for object matchingMohamed F. GafarElsayed E. HemayedMatching 3D objects by their similarity is a fundamental problem in computer vision, computer graphics and many other fields. The main challenge in object matching is to find a suitable shape representation that can be used to accurately and quickly discriminate between similar and dissimilar shapes. In this paper we present a new volumetric descriptor to represent 3D objects. The proposed descriptor is used to match objects under rigid transformations including uniform scaling. The descriptor represents the object by dividing it into shells, acquiring the area distribution of the object through those shells. The computed areas are normalised to make the descriptor scale-invariant in addition to rotation and translation invariant. The effectiveness and stability of the proposed descriptor to noise and variant sampling density as well as the effectiveness of the similarity measures are analysed and demonstrated through experimental results.http://www.sciencedirect.com/science/article/pii/S20901232100007183D object recognitionVolumetric descriptorSurface area distributionShape matching
spellingShingle Mohamed F. Gafar
Elsayed E. Hemayed
Surface Area Distribution Descriptor for object matching
Journal of Advanced Research
3D object recognition
Volumetric descriptor
Surface area distribution
Shape matching
title Surface Area Distribution Descriptor for object matching
title_full Surface Area Distribution Descriptor for object matching
title_fullStr Surface Area Distribution Descriptor for object matching
title_full_unstemmed Surface Area Distribution Descriptor for object matching
title_short Surface Area Distribution Descriptor for object matching
title_sort surface area distribution descriptor for object matching
topic 3D object recognition
Volumetric descriptor
Surface area distribution
Shape matching
url http://www.sciencedirect.com/science/article/pii/S2090123210000718
work_keys_str_mv AT mohamedfgafar surfaceareadistributiondescriptorforobjectmatching
AT elsayedehemayed surfaceareadistributiondescriptorforobjectmatching