Partitioning-based face recognition using PCA, LDA and ICA - Toygar, Önsen; Acan, Adnan (My University, 2005)
Partitioning approaches for facial images are presented for the improvement of the recognition performance of appearance-based statistical methods Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA). A face image is partitioned into several equal-width vertical or horizontal segments and a multiple classifier based divide-and-conquer approach is used to combine the recognition results associated with these segments to recognize the whole face. The experiments demonstrate that vertical and horizontal partitioning result in a better recognition performance compared to the performance results of the holistic PCA, LDA and ICA methods.
Keywords: Appearance-based statistical methods; Classifier combination; Feature-based face recognition; ICA; LDA; Multiple classier systems; PCA