Abstract
In this paper, a video-based approach for camera scene registration in augmented reality systems is presented. The presented technique relies on the definition of a model, which is derived from an appropriate parametric linear optimization problem. The optimal parameters are sought in the solution space defined by physical meaningful constraints. Solving the underlying regularized linear problem we expect to overcome the major shortcoming observed in image-based augmented reality and tele-presence systems: the extreme lack of robustness due to the ill-posed nature of the calibration problem. Several computer experiments have been conducted in order to assess the performance of the introduced technique.