关键词: 人脸识别, 自适应主元提取, 形变模型

Abstract: An improved adaptive principal component extraction algorithm based face recognition method is proposed in this paper. Improved adaptive principal component extraction algorithm is applied to project facial images from high-dimensional observation space to low-dimensional feature space. The weight-value updating equation of feed-forward network is improved to decrease the computational complexity. Region filling and hidden-surface removal algorithms are adopted to generate multiple virtual samples according to single facial image based on 3D face morphable model which is adopted to tackle the small sample size problem. Experimental results on ORL and UMIST face database show that our method makes impressive performance improvement compared with conventional Eigenface and Fisherface methods.

Key words: Face Recognition, Adaptive Principal Component Extraction, Morphable Model