On the equivalence of variational and statistical differential motion estimation

In this contribution, we examine variational based motion estimation techniques, e.g. (B. Horn and B. Schunck, 1981), (A. Bruhn, et al., 2005), from a statistical point of view. The fact that all deterministic motivated methods can be described in a Bayesian framework allows the understanding of the physical meaning of the parameters which occur as free parameters in the deterministic framework. Furthermore, these parameters can directly be estimated from observable data when choosing the statistical point of view. The estimation of the optimal regularization parameter is demonstrated to work successfully on image sequences with known ground truth