Progressive Principal Component Analysis
نویسندگان
چکیده
Principal Component Analysis (PCA) is a feature extraction approach directly based on a whole vector pattern and acquires a set of projections that can realize the best reconstruction for an original data in the mean squared error sense. In this paper, the progressive PCA (PrPCA) is proposed, which could progressively extract features from a set of given data with large dimensionality and the extracted features are subsequently applied to pattern recognition. Experiments on the FERET database show its face recognition performance is better than those based on both E(PC)A and FLDA.
منابع مشابه
Principal component analysis or factor analysis different wording or methodological fault?
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