Grid-based multi-scale PCA method for face recognition in the large face database

Abstract

In this paper, we propose an efficient grid-based multi-scale PCA method in the large face database. This method divides the large face database into some small sub-face databases by maximizing the variance in the face subdatabase and minimizing the variance between the face sub-databases, then it segments the recognition process into the local coarse profile recognition process and accurate detailed geometric sub-component analysis process, and assigns the local coarse profile recognition process to the nodes of the multimedia service grid to reduce the recognition time. Our experimental results show that with the increase of the face database, this method not only reduces the recognition time, but also remarkably increases the recognition precision, compared with other PCA methods. © Springer-Verlag Berlin Heidelberg 2006.