Evolutionary computation applied to mesh optimization of a 3-D facial image

We apply evolutionary algorithms to the approximation of a three-dimensional image of a human face using a triangular mesh. The problem is how to locate a limited number of node points such that the mesh approximates the facial surface as closely as possible. Two evolutionary algorithms are implemented and compared. The first does selection and reproduction in the population of node points in a single triangulation. The second is a genetic algorithm in which a set of different triangulations is regarded as a population. We expect that such evolutionary computation can be used in other engineering applications which share the same problem of surface approximation