Multiview reconstruction of space curves
(2003) IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, 2003 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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/611933
- author
- Kahl, Fredrik LU and August, Jonas
- organization
- publishing date
- 2003
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Stereo algorithms, Piecewise constant image, Curve extraction
- host publication
- 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
- conference location
- Nice, France
- conference dates
- 2003-10-13 - 2003-10-16
- 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
- 2016-04-04 10:17:40
- date last changed
- 2022-02-28 18:10:12
@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}},
keywords = {{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}},
doi = {{10.1109/ICCV.2003.1238461}},
volume = {{2}},
year = {{2003}},
}