Non-Parametric Self-Calibration

In this paper we develop a theory of non-parametric self-calibration. Recently, schemes have been devised for non-parametric laboratory calibration, but not for selfcalibration. We allow an arbitrary warp to model the intrinsic mapping, with the only restriction that the camera is central and that the intrinsic mapping has a well-defined non-singular matrix derivative at a finite number of points under study

Using Galois Theory to Prove Structure from Motion Algorithms are Optimal

This paper presents a general method, based on Galois Theory, for establishing that a problem can not be solved by a ′machine ′ that is capable of the standard arithmetic operations, extraction of radicals (that is, m-th roots for any m), as well as