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Embedded Voxel Colouring
Leung, Carlos W. Y., Appleton, Ben and Sun, Changming (2003). Embedded Voxel Colouring. In: Sun, Changming, Talbot, Hugues, Ourselin, Sebastien and Adriaansen, Tony, Digital Image Computing: Techniques and Applications. Digital Image Computing: Techniques and Applications, Sydney, (623-632). 10 December, 2003.
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| Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials) |
| Name |
Description |
MIMEType |
Size |
Downloads |
EVC.pdf
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EVC.pdf |
application/pdf |
306.79KB |
273 |
| Author(s) |
Leung, Carlos W. Y.
Appleton, Ben
Sun, Changming
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| Title of paper |
Embedded Voxel Colouring
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| Conference name |
Digital Image Computing: Techniques and Applications
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| Conference location |
Sydney
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| Conference dates |
10 December, 2003
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| Proceedings title |
Digital Image Computing: Techniques and Applications
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| Editor(s) |
Sun, Changming
Talbot, Hugues
Ourselin, Sebastien
Adriaansen, Tony
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| Place published |
Sydney
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| Publisher |
CSIRO
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| Publication date |
2003
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| Volume number |
2
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| ISBN |
1-74107-043-0
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| Start page |
623
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| End page |
632
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| Total pages |
10
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| Language |
eng
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| Abstract/Summary |
The reconstruction of a complex scene from multiple images is a fundamental problem in the field of computer vision. Volumetric methods have proven to be a strong alternative to traditional correspondence-based methods due to their flexible visibility models. In this paper we analyse existing methods for volumetric reconstruction and identify three key properties of voxel colouring algorithms: a water-tight surface model, a monotonic carving order, and causality. We present a new Voxel Colouring algorithm which embeds all reconstructions of a scene into a single output. While modelling exact visibility for arbitrary camera locations, Embedded Voxel Colouring removes the need for a priori threshold selection present in previous work. An efficient implementation is given along with results demonstrating the advantages of posteriori threshold selection.
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| Subjects |
280208 Computer Vision
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| Keyword(s) |
iris-research
reconstruction
3D
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