Performance evaluation of face recognition using frames of ten pose angles

Abstract

Face recognition has received much attention recently in the biometrics research. Many studies have shown improvement in recognition rate when 2D and 3D faces were combined. However, the use of the 3D face has a few limitations such as that the 3D data requires much more storage space and long processing time. Therefore, there is a strong interest to explore new methods that can provide similar or better results in the face recognition. This thesis presents an experimental study by using a sequence of rotating head videos under two different lighting conditions, regular indoor lighting and strong shadow lighting. The experiment were carried out using two sets of data, the first set of over 100 subjects and the second set of 47 subjects. Very promising results have been observed in terms of the recognition performance measured by the cumulative characteristics curves.