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Multiview reconstruction of space curves

Kahl, Fredrik LU and August, Jonas (2003) IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, 2003 In Proceedings of the IEEE International Conference on Computer Vision 2. p.1017-1024
Abstract
Is the real problem in resolving correspondence using current stereo algorithms the lack of the "right" matching criterion? In studying the related task of reconstructing three-dimensional space curves from their projections in multiple views, we suggest that the problem is more basic: matching and reconstruction are coupled, and so reconstruction algorithms should exploit ths rather than assuming that matching can be successfully performed before reconstruction. To realize this coupling, a generative model of curves is introduced which has two key components: (i) a prior distribution of general space curves and (ii) an image formation model whch discribes how 3D curves are projected onto the image plane. A novel aspect of the image... (More)
Is the real problem in resolving correspondence using current stereo algorithms the lack of the "right" matching criterion? In studying the related task of reconstructing three-dimensional space curves from their projections in multiple views, we suggest that the problem is more basic: matching and reconstruction are coupled, and so reconstruction algorithms should exploit ths rather than assuming that matching can be successfully performed before reconstruction. To realize this coupling, a generative model of curves is introduced which has two key components: (i) a prior distribution of general space curves and (ii) an image formation model whch discribes how 3D curves are projected onto the image plane. A novel aspect of the image formation model is that it uses an exact description of the gradient field of a piecewise constant image. Based on this forward model, a fully automatic algorithm for solving the inverse problem is developed for an arbitrary number of views. The resulting algorithm is robust to partial occlusion, deficiencies in image curve extraction and it does not rely on photometric information. The relative motion of the cameras is assumed to be given. Several experiments are carried out on various realistic scenarios. In particular, we focus on scenes where traditional correlation-based methods would fail. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Stereo algorithms, Piecewise constant image, Curve extraction
in
Proceedings of the IEEE International Conference on Computer Vision
volume
2
pages
1017 - 1024
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, 2003
external identifiers
  • wos:000186833000135
  • other:CODEN: PICVES
  • scopus:0344120679
DOI
10.1109/ICCV.2003.1238461
language
English
LU publication?
yes
id
f8c38524-5f9c-4d83-9fd7-1ce679bffe87 (old id 611933)
date added to LUP
2007-11-30 11:50:24
date last changed
2017-01-08 05:37:23
@inproceedings{f8c38524-5f9c-4d83-9fd7-1ce679bffe87,
  abstract     = {Is the real problem in resolving correspondence using current stereo algorithms the lack of the "right" matching criterion? In studying the related task of reconstructing three-dimensional space curves from their projections in multiple views, we suggest that the problem is more basic: matching and reconstruction are coupled, and so reconstruction algorithms should exploit ths rather than assuming that matching can be successfully performed before reconstruction. To realize this coupling, a generative model of curves is introduced which has two key components: (i) a prior distribution of general space curves and (ii) an image formation model whch discribes how 3D curves are projected onto the image plane. A novel aspect of the image formation model is that it uses an exact description of the gradient field of a piecewise constant image. Based on this forward model, a fully automatic algorithm for solving the inverse problem is developed for an arbitrary number of views. The resulting algorithm is robust to partial occlusion, deficiencies in image curve extraction and it does not rely on photometric information. The relative motion of the cameras is assumed to be given. Several experiments are carried out on various realistic scenarios. In particular, we focus on scenes where traditional correlation-based methods would fail.},
  author       = {Kahl, Fredrik and August, Jonas},
  booktitle    = {Proceedings of the IEEE International Conference on Computer Vision},
  keyword      = {Stereo algorithms,Piecewise constant image,Curve extraction},
  language     = {eng},
  pages        = {1017--1024},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Multiview reconstruction of space curves},
  url          = {http://dx.doi.org/10.1109/ICCV.2003.1238461},
  volume       = {2},
  year         = {2003},
}