Local and Global Feature Extraction for Face Recognition

Abstract

This paper proposes a new feature extraction method for face recognition. The proposed method is based on Local Feature Analysis (LFA). LFA is known as a local method for face recognition since it constructs kernels which detect local structures of a face. It, however, addresses only image representation and has a problem for recognition. In the paper, we point out the problem of LFA and propose a new feature extraction method by modifying LFA. Our method consists of three steps. After extracting local structures using LFA, we construct a subset of kernels, which is efficient for recognition. Then we combine the local structures to represent them in a more compact form. This results in new bases which have compromised aspects between kernels of LFA and eigenfaces for face images. Through face recognition experiments, we verify the efficiency of our method.KeywordsFeature ExtractionFace RecognitionFace ImageReconstruction ErrorFeature Extraction MethodThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.