Interpolationfaces method and its applications for face recognition

This paper puts forward to a new and valid Interpolationfaces method which combines interpolation method with Linear Discriminative Analysis (LDA) for face image recognition. After availability verification of this method, Comparison experiment of Interpolationfaces and Eigenfaces method which is based on Principle Component Analysis(PCA) dimension reduction is accomplished and better recognition rate is obtained by this Interpolationfaces method. Fusion of different interpolation methods are designed, which provides good base to select proper interpolation methods and their combination type for Interpolationfaces method. Moreover the reason why this kind of Interpolationfaces method can obtain better results than PCA is basically analyzed. Interpolationfaces method has clear mathematics foundation and is very simple, which has great potential value in face recognition applications.