Human face recognition and the face image set's topology
CVGIP: Image Understanding
Relative Affine Structure: Canonical Model for 3D From 2D Geometry and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
From 2D Images to 3D Face Geometry
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
View-Invariant Face Detection Method Based on Local PCA Cells
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Journal of Cognitive Neuroscience
Matching pursuit filters applied to face identification
IEEE Transactions on Image Processing
Face recognition/detection by probabilistic decision-based neural network
IEEE Transactions on Neural Networks
Practical error analysis of cross-ratio-based planar localization
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
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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.