A Comparative Study of Face Feature Metrics for a Dynamic and Self-Organised Multimedia Indexing Tool

Abstract

In this study, Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) methods are integrated into MUVIS, a
remarkable multimedia indexing and classification system with an effective indexing structure, for face recognition problem. Their
classification performance is compared with that of Gabor Filter which already exists in MUVIS via proposed performance metric. It has been
observed that, as far as the classification performance in MUVIS is concerned, LDA performs slightly better than Gabor filter whereas PCA is
the worst among them