Comparative Study of Principal Component Analysis and Independent Component Analysis
نویسندگان
چکیده
Face recognition is emerging as an active research area with numerous commercial and law enforcement applications. This paper presents comparative analysis of two most popular subspace projection techniques for face recognition. It compares Principal Component Analysis (PCA) and Independent Component Analysis (ICA), as implemented by the InfoMax algorithm. ORL face database is used for training and testing of the system. The results show that for the task of face recognition, ICA outperforms PCA in terms of recognition rate and subspace dimensionality.
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تاریخ انتشار 2014