In this paper a nonlinear optimization technique for active appearance 
models is proposed. This approach allowed the model to be more robust 
to initialization position of the model and slightly decrease computational 
complexity of singular optimization step. Experimental result are obtained 
and compared to performance of conventional active appearance models.