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-List Of Titles -Embedded voxel colouring with adaptive threshold selection using globally minimal surfaces

Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/184088

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Title
Embedded voxel colouring with adaptive threshold selection using globally minimal surfaces
Related
International journal of computer vision, Vol. 99, No. 2, (2012), p.215-231
DOI
10.1007/s11263-012-0525-8
Publisher
Springer
Date
2012
Author/Creator
Leung, Carlos
Author/Creator
Appleton, Ben
Author/Creator
Buckley, Mitchell
Author/Creator
Sun, Changming
Description
Image-based 3D reconstruction remains a competitive field of research as state-of-the-art algorithms continue to improve. This paper presents a voxel-based algorithm that adapts the earliest space-carving methods and utilises a minimal surface technique to obtain a cleaner result. Embedded Voxel Colouring is built in two stages: (a) progressive voxel carving is used to build a volume of embedded surfaces and (b) the volume is processed to obtain a surface that maximises photo-consistency data in the volume. This algorithm combines the strengths of classical carving techniques with those of minimal surface approaches. We require only a single pass through the voxel volume, this significantly reduces computation time and is the key to the speed of our approach. We also specify three requirements for volumetric reconstruction: monotonic carving order, causality of carving and water-tightness. Experimental results are presented that demonstrate the strengths of this approach.
Description
17 page(s)
Subject Keyword
Causality of carving
Subject Keyword
Embedded voxel colouring
Subject Keyword
Globally minimal surfaces
Subject Keyword
Monotonic carving order
Subject Keyword
Volumetric 3D reconstruction
Subject Keyword
Water-tightness
Resource Type
journal article
Organisation
Macquarie University. Dept. of Mathematics

Identifier
http://hdl.handle.net/1959.14/184088
Identifier
ISSN:0920-5691
Identifier
mq_res-ext-2-s2.0-84863630708
Language
eng
Reviewed
Reviewed
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Citation Format
E-mail Address
Subject
"International journal of computer vision"
 
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