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Generalized N-Dimensional Principal Component Analysis (GND-PCA) Based Statistical Appearance Modeling of Facial Images with Multiple Modes
IPSJ Transactions on Computer Vision and Applications
This paper introduces a framework called generalized N-dimensional principal component analysis (GND-PCA) for statistical appearance modeling of facial images with multiple modes including different people, different viewpoint and different illumination. The facial images with multiple modes can be considered as high-dimensional data. GND-PCA can represent the highorder dimensional data more efficiently. We conduct extensive experiments on MaVIC Database (KAO-Ritsumeikan Multi-angle View,doi:10.2197/ipsjtcva.1.231 fatcat:t6fclvt4fnb5fjsqebrwmlpbcy