  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 many enough 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.
