Abstract

As it has been noted several times in literature, the difficult part of autocalibration efforts resides in the structural non-linearity of the search for the plane at infinity. In this paper we present a robust and versatile autocalibration method based on the enumeration of the inher- ently bounded space of the intrinsic parameters of two cameras in order to find the collineation of space that upgrades a given pro jective recon- struction to Euclidean. Each sample of the search space (which reduces to 2 under mild assumptions) defines a consistent plane a finite subset of R at infinity. This in turn produces a tentative, approximate Euclidean upgrade of the whole reconstruction which is then scored according to the expected intrinsic parameters of a Euclidean camera. This approach has been compared with several other algorithms on both synthetic and concrete cases, obtaining favourable results.