An energy minimization approach to dense stereovision

This work presents the realization of a general system of dense stereovision by simulated annealing. Dense stereovision is based on point matching. We show the performance of our approach compared to correlation. We use an optimization method in order to take into consideration the global aspect of the problem, as opposed to the correlation that acts locally on windows, and be able to incorporate this module with other early vision modules. The stereovision problem is an ill-posed problem where the global minimum is hidden by local minima and where the notion of gradient does not exist. For this reason, the simulated annealing algorithm seems the most suitable to solve the stereovision problem. The constraints of the stereovision problem are expressed by an energy function and elementary transformations