Computer Engineering Commons^™

The Gaussian Orthogonal Laplacianfaces Modelling In Feature Space For Facial Image Recognition, Arif Muntasa

Makara Journal of Technology

Dimensionality reduction based on appearance has been interesting issue on the face image research fields. Eigenface and Fisherface are linear techniques based on full spectral features, for both Eigenface and Fisherface produce global manifold structure. Inability of them in yielding local manifold structure have been solved by Laplacianfaces and further improved by Orthogonal Laplacianfaces, so it can yield orthogonal feature vectors. However, they have also a weakness, when training set samples have non-linear distribution. To overcome this weakness, feature extraction through data mapping from input to feature space using Gaussian kernel function is proposed. To avoid singularity, the Eigenface decomposition …