Face Feature Extraction Based on Overcomplete ICA Feature Extraction
基于Overcomplete ICA的人脸特征提取

Face feature extraction is the key procedure in face recognition. An important approach of face extraction is to face a set of base images, then represent faces as a linear combination of those base images. During the procedure of finding base images using PCA and ICA, the number of source images is equal to base images. In the paper, we present a face feature extraction approach, which gain the the number base images is lager than source images. At the end of thts paper, we give a face recognition examination using Overcomplete ICA feture extraction and shortest dis- tant separation, and compare the result with PCA and ICA.