PCA-SIFT is an extension to SIFT which aims to reduce SIFT’s high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminati...
—In this paper, we propose a Multi-Manifold Discriminant Analysis (MMDA) method for face feature extraction and face recognition, which is based on graph embedded learning and un...
In this paper, we investigate the behavior of Gabor responses at automatically located facial feature points for face recognition. In our approach, a set of feature points on the ...
Many state-of-the-art face recognition algorithms use image descriptors based on features known as Local Binary Patterns (LBPs). While many variations of LBP exist, so far none of ...
Face recognition is a challenging field of research not only because of the complexity of this subject, but also because of its numerous practical applications. Much progress has ...
Walid Riad Boukabou, Lahouari Ghouti, Ahmed Bourid...