Different eigenspace-based approaches have been proposed for the recognition of faces. They differ mostly in the kind of projection method been used and in the similarity matching ...
The most expressive way humans display emotions is through facial expressions. Humans detect and interpret faces and facial expressions in a scene with little or no effort. Still, ...
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
Linear Discriminant Analysis (LDA) is a popular feature extraction technique for face recognition. However, It often suffers from the small sample size problem when dealing with t...
Abstract. The performance of face recognition systems that use twodimensional images is dependent on consistent conditions such as lighting, pose, and facial appearance. We are dev...