Multi-Eigenspace Learning for Video-Based Face Recognition.
ABSTRACT In this paper, we propose a novel online learning method called Multi-Eigenspace Learning which can learn appearance models
incrementally from a given video stream. For each subject, we try to learn a few eigenspace models using IPCA (Incremental
Principal Component Analysis). In the process of Multi-Eigenspace Learning, each eigenspace generally contains more and more
samples except one eigenspace which contains the least number of samples. Then, these learnt eigenspace models are used for
video-based face recognition. Experimental results show that the proposed method can achieve high recognition rate.