It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
Jie Wang, Konstantinos N. Plataniotis, Anastasios ...
The Principal Components Analysis (PCA) is one of the most successfull techniques that have been used to recognize faces in images. This technique consists of extracting the eigenv...
In this paper we evaluate the effectiveness of two likelihood normalization techniques, the Background Model Set (BMS) and the Universal Background Model (UBM), for improving perf...
We present a promising analysis on using the pattern of symmetry in the face to increase the accuracy of three-dimensional face recognition. We introduce the concept of the ‘ave...
: Recently, a method called (PC)2 A was proposed to deal with face recognition with one training image per person. As an extension of the standard eigenface technique, (PC)2 A comb...