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Fusion of PCA-Based and LDA-Based Similarity Measures for Face Verification
EURASIP Journal on Advances in Signal Processing
The problem of fusing similarity measure-based classifiers is considered in the context of face verification. The performance of face verification systems using different similarity measures in two well-known appearance-based representation spaces, namely Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) is experimentally studied. The study is performed for both manually and automatically registered face images. The experimental results confirm that our optimiseddoi:10.1155/2010/647597 fatcat:ybemuu335vdbzalno3rwxrwbmm