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Reconstruction from Image Sequences by means of Relative Depths

Heyden, Anders LU (1995) IEEE International Conference on Computer Vision, 1995 In Fifth International Conference on Computer Vision, 1995. Proceedings. p.1058-1063
Abstract
The paper deals with the problem of reconstructing the locations of n points in space from m different images without camera calibration. It shows how these problems can be put into a similar theoretical framework. A new concept, the reduced fundamental matrix, is introduced. It contains just 4 parameters and can be used to predict locations of points in the images and to make reconstruction. We also introduce the concept of reduced fundamental tensor which describes the relations between points in 3 images. It has 15 components and depends on 9 parameters. Necessary and sufficient conditions for a tensor to be a reduced fundamental tensor are derived. This framework can be generalised to a sequence of images. The dependencies between the... (More)
The paper deals with the problem of reconstructing the locations of n points in space from m different images without camera calibration. It shows how these problems can be put into a similar theoretical framework. A new concept, the reduced fundamental matrix, is introduced. It contains just 4 parameters and can be used to predict locations of points in the images and to make reconstruction. We also introduce the concept of reduced fundamental tensor which describes the relations between points in 3 images. It has 15 components and depends on 9 parameters. Necessary and sufficient conditions for a tensor to be a reduced fundamental tensor are derived. This framework can be generalised to a sequence of images. The dependencies between the different representations are investigated. Furthermore a canonical form of the camera matrices in a sequence are presented (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
image reconstruction, image sequences, matrix algebra, tensors
in
Fifth International Conference on Computer Vision, 1995. Proceedings.
pages
1058 - 1063
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE International Conference on Computer Vision, 1995
external identifiers
  • Scopus:0029215683
ISBN
0-8186-7042-8
DOI
10.1109/ICCV.1995.466817
language
English
LU publication?
yes
id
fc16dad7-4c5c-493d-8405-1c49a019a2d1 (old id 787275)
alternative location
http://ieeexplore.ieee.org/iel2/3245/9796/00466817.pdf?tp=&arnumber=466817&isnumber=9796
date added to LUP
2008-03-31 13:12:16
date last changed
2016-08-03 13:42:17
@misc{fc16dad7-4c5c-493d-8405-1c49a019a2d1,
  abstract     = {The paper deals with the problem of reconstructing the locations of n points in space from m different images without camera calibration. It shows how these problems can be put into a similar theoretical framework. A new concept, the reduced fundamental matrix, is introduced. It contains just 4 parameters and can be used to predict locations of points in the images and to make reconstruction. We also introduce the concept of reduced fundamental tensor which describes the relations between points in 3 images. It has 15 components and depends on 9 parameters. Necessary and sufficient conditions for a tensor to be a reduced fundamental tensor are derived. This framework can be generalised to a sequence of images. The dependencies between the different representations are investigated. Furthermore a canonical form of the camera matrices in a sequence are presented},
  author       = {Heyden, Anders},
  isbn         = {0-8186-7042-8},
  keyword      = {image reconstruction,image sequences,matrix algebra,tensors},
  language     = {eng},
  pages        = {1058--1063},
  publisher    = {ARRAY(0x90145c8)},
  series       = {Fifth International Conference on Computer Vision, 1995. Proceedings.},
  title        = {Reconstruction from Image Sequences by means of Relative Depths},
  url          = {http://dx.doi.org/10.1109/ICCV.1995.466817},
  year         = {1995},
}