Abstract for broadhurst_cvpr99

Proc. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition


A. Broadhurst and R. Cipolla

June 1999

The object of this paper is to find a quick and accurate method for computing the projection matrices of an image sequence, so that the error is distributed evenly along the sequence.

It assumes that a set of correspondences between points in the images is known, and that these points represent rigid points in the world. This paper extends the algebraic minimisation approach developed by Hartley so that it can be used for long image sequences. This is achieved by initially computing a trifocal tensor using the three most extreme views. The intermediate views are then computed linearly using the trifocal tensor. An iterative algorithm is presented which perturbs the twelve entries of one camera matrix so that the algebraic error along the whole sequence is minimised.

(ftp:) broadhurst_cvpr99.ps.gz (http:) broadhurst_cvpr99.ps.gz
PDF (automatically generated from original PostScript document - may be badly aliased on screen):
  (ftp:) broadhurst_cvpr99.pdf | (http:) broadhurst_cvpr99.pdf

If you have difficulty viewing files that end '.gz', which are gzip compressed, then you may be able to find tools to uncompress them at the gzip web site.

If you have difficulty viewing files that are in PostScript, (ending '.ps' or '.ps.gz'), then you may be able to find tools to view them at the gsview web site.

We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.