Optimised landmark model matching for face recognition

Abstract

A new method for face recognition, landmark model matching, is proposed in this paper. It is based on the concepts of elastic bunch graph matching and active shape model, and optimised with particle swarm optimisation. It is a fully automatic algorithm and can be used for face databases where only one image per person is available. A face is represented by a landmark model consisting of nodes labelled with jets and gray-level profiles. A landmark distribution model is created from a few training images. The model similarity between the landmark distribution model and the deformable landmark model that has to be fitted to the face in the image is maximised by particle swarm optimisation, to find the optimal model to represent the face. Improved results were obtained by this method compared with elastic bunch graph matching without optimisation