Linear projections from ℙ^k to ℙ^h appear in computer vision as models of images of dynamic or segmented scenes. Given multiple projections of the same scene, the identification of sufficiently many correspondences between the images allows, in principle, to reconstruct the position of the projected objects. A critical locus for the reconstruction problem is a variety in ℙ^k containing the set of points for which the reconstruction fails. Critical loci turn out to be determinantal varieties. In this paper we determine and classify all the smooth critical loci, showing that they are classical projective varieties.

Smooth determinantal varieties and critical loci in multiview geometry

R. Notari;
2022-01-01

Abstract

Linear projections from ℙ^k to ℙ^h appear in computer vision as models of images of dynamic or segmented scenes. Given multiple projections of the same scene, the identification of sufficiently many correspondences between the images allows, in principle, to reconstruct the position of the projected objects. A critical locus for the reconstruction problem is a variety in ℙ^k containing the set of points for which the reconstruction fails. Critical loci turn out to be determinantal varieties. In this paper we determine and classify all the smooth critical loci, showing that they are classical projective varieties.
2022
Determinantal varieties · Minimal degree varieties · Multiview geometry · Critical loci
File in questo prodotto:
File Dimensione Formato  
Bertolini2021_Article_SmoothDeterminantalVarietiesAn.pdf

accesso aperto

: Publisher’s version
Dimensione 1.65 MB
Formato Adobe PDF
1.65 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1196937
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 1
social impact