An Improved Face Recognition Method Based on Filled Function

Abstract

3D data registration and classifier are two important components in face recognition system. Aiming at the handicaps in current methods such as slow convergence or easiness of getting into local optimization, this paper works out a novel face recognition method combining filled function method, which can find a lower local minimizer by leaving the local minimizer previously found. By repeating these processes, a global minimizer can be obtained at last. Then it works out an improved ICP 3D data registration algorithm and an improved BP neural network classifier. Experiments show that this face recognition method decreases the amount of calculation, improves the accuracy of recognition precision and has an actual recognition effect.