This paper deals with the problem of evaluating the uncertainties associated with nonlinear camera model based stereo reconstruction using the law of propagation of uncertainty. The procedure of stereo reconstruction involves two consecutive stages: calibrating camera models and reconstructing a 3D point from its image projections. The output quantities of the first stage

the parameters of camera models

constitute a part of the input quantities of the second stage. The analytical expressions for uncertainty propagation during reconstructing a 3D point are proposed. At last

the results of an experiment with synthetic data are validated using Monte Carlo Simulation

and some typical application examples are presented.