We numerically investigate a mean-field Bayesian approach with the assistance
of the Markov chain Monte Carlo method to estimate motion velocity fields and
probabilistic models simultaneously in consecutive digital images described by
spatio-temporal Markov random fields. Preliminary to construction of our
procedure, we find that mean-field variables in the iteration diverge due to
improper normalization factor of regularization terms appearing in the
posterior.