The point distribution model is a powerful shape description technique and has enormous applications in a short time

especially for flexible or deformable model analysis in images. Initially

a model is generatively built by statistical analysis from a number of examples. In some applications

nevertheless

it allows building a set of models or continuous sequence of models since a single one is not well representing a highly changing object. This paper presents a method to compute such a middle time-point model which is formed from two neighboring models in runtime. In case of linear algorithm

the model parameters that have already given by PCA are determined in several steps. The methodology is validated with both computer simulation and practical experiments. Results indicate that it is worthwhile for its adoption in some complex modeling applications.