A new video sequence of faces can be generated from the model as follows. First, given an history of generated sub-trajectory groups, one can find the longest memory encoded in the variable length Markov model tree. Thus the probability of generating a new group can be read directly from the tree, if it is encoded in the tree. The probabilities not encoded in the tree are small probabilities, that we can approximate by a uniform distribution. After having fetched the probabilities of generation of each sub-trajectory groups, we sample from this set of probabilities to generate the next sub-trajectory group. We then generate new parameters by sampling from a Gaussian distribution. The new sub-trajectory can then be generated given equation 1. All the sub-trajectories generated are then concatenated. This gives a sequence of appearance parameters. The video sequence can then be generated by synthesising those parameters into a face as described in section 3.1.