Face Detection Based on Template Matching and 2DPCA Algorithm

Human face recognition technology is a popular research topic in the biometrics identification area. Face detection is the most important pre-processing module of a face recognition system, and it plays an important role in applications such as video surveillance, human computer interface. The purpose of the face detection is to search and orient faces in images in complex background. In this paper, we propose a hierarchical face detection method by using the template matching algorithm and 2DPCA algorithm. The method includes two different classifiers. The first one is called rough classifier, which filtrates the most of the non-face. The second one is a core classifier, which uses 2DPCA algorithm to detect the face based on the result from the first classifier. The results of the experiment indicates that we implement hierarchical detection to face images not only improves the accurate rate of the face detection, but also shortens detection time greatly.