A Fully Projective Error Model for Visual Reconstruction - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Other Publications Year : 1995

A Fully Projective Error Model for Visual Reconstruction


Measurement uncertainty is a recurrent concern in visual reconstruction. Image formation and 3D structure recovery are essentially projective processes that do not quite fit into the classical framework of affine least squares, so intrinsically projective error models must be developed. This paper describes initial theoretical work on a fully projective generalization of affine least squares. The result is simple and projectively natural and works for a wide variety of projective objects (points, lines, hyperplanes, and so on). The affine theory is contained as a special case, and there is also a canonical probabilistic interpretation along the lines of the classical leastsquares/ Gaussian/approximate log-likelihood connection. Standard linear algebra often suffices for practical calculations.
Fichier principal
Vignette du fichier
Triggs-scenerep95.pdf (154.45 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

inria-00548381 , version 1 (20-12-2010)


  • HAL Id : inria-00548381 , version 1


Bill Triggs. A Fully Projective Error Model for Visual Reconstruction. 1995. ⟨inria-00548381⟩
123 View
83 Download


Gmail Facebook X LinkedIn More