Identity verification by relative 3-D structure using multiple facial images

Identity verification is one of the critical issues in the sector of security and has been emerging as an active research area. In recent years, technologies using biological features to address problems of identity verification have attracted numerous research interests. For examples, fingerprint recognition, voice recognition and pattern of blood vessels in the retina have spanned many commercial applications. However, special and expensive equipments such as fingerprint readers and iris scanners are often required and people have to be in unpleasant poses occasionally. This paper presents a study on computer vision technique and its application in face recognition to achieve identity verification. With multiple facial images taken from different view angles, relative affine structures are computed and are used as measurements. To that end, the explicit relationship between relative affine structure and the cross ratio which is a view-invariant under perspective projection is also addressed. The proposed method neither requires camera calibration nor reconstructs 3D models. According to simulation results, the developed approach can achieve satisfactory results given the feature points of facial images.