Reconstruction from Image Sequences by means of Relative Depths
(1995) IEEE International Conference on Computer Vision, 1995 In Fifth International Conference on Computer Vision, 1995. Proceedings. p.10581063 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:
http://lup.lub.lu.se/record/787275
 author
 Heyden, Anders ^{LU}
 organization
 publishing date
 1995
 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
 IEEEInstitute of Electrical and Electronics Engineers Inc.
 conference name
 IEEE International Conference on Computer Vision, 1995
 external identifiers

 scopus:0029215683
 ISBN
 0818670428
 DOI
 10.1109/ICCV.1995.466817
 language
 English
 LU publication?
 yes
 id
 fc16dad74c5c493d84051c49a019a2d1 (old id 787275)
 alternative location
 http://ieeexplore.ieee.org/iel2/3245/9796/00466817.pdf?tp=&arnumber=466817&isnumber=9796
 date added to LUP
 20080331 13:12:16
 date last changed
 20170326 04:36:18
@inproceedings{fc16dad74c5c493d84051c49a019a2d1, 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}, booktitle = {Fifth International Conference on Computer Vision, 1995. Proceedings.}, isbn = {0818670428}, keyword = {image reconstruction,image sequences,matrix algebra,tensors}, language = {eng}, pages = {10581063}, publisher = {IEEEInstitute of Electrical and Electronics Engineers Inc.}, title = {Reconstruction from Image Sequences by means of Relative Depths}, url = {http://dx.doi.org/10.1109/ICCV.1995.466817}, year = {1995}, }