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Distinctive representations for the recognition of curved surfaces using outlines and markings

Abstract:
Recognising 3D objects from single images presents a range of significant problems, mostly to do with the nature and distinctiveness of the representations that can be recovered. In such special cases as polyhedra, surfaces of revolution, general cones, canal surfaces and algebraic surfaces, the geometry can be recovered with varying degrees of success and of ambiguity. We discuss these volumetric primitives, comparing their utility to that of surface primitives.
For a model based recognition system, representation is not simply concerned with particular geometric primitives, but the entire recognition process. In our view, representations should be motivated by the way quantities that are measurable in an image influence decisions throughout the recognition process.
When some geometric information is available, its potential distinctiveness can often be substantially enhanced by constructing representations that capture surface markings in an appropriate frame on the surface itself.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/3-540-60477-4_6

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0002-8945-8573


Publisher:
Springer
Host title:
Object Representation in Computer Vision: International NSF-ARPA Workshop, New York City, NY, USA, December 5 - 7, 1994. Proceedings
Pages:
89-99
Series:
Lecture Notes in Computer Science
Series number:
994
Place of publication:
Berlin, Heidelberg
Publication date:
2005-06-01
Event title:
International NSF-ARPA Workshop on Object Representation in Computer Vision
Event location:
New York City, NY, USA
Event start date:
1994-12-05
Event end date:
1994-12-07
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
EISBN:
9783540475262
ISBN:
9783540604778


Language:
English
Keywords:
Pubs id:
1770603
Local pid:
pubs:1770603
Deposit date:
2024-07-29

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