Invariant Descriptors for 3D Object Recognition and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Model-based invariants for 3-D vision
International Journal of Computer Vision
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition: The Problem of Compensating for Changes in Illumination Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Component-Based SVM Classification and Morphable Models
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
Expression-invariant 3D face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
IEEE Transactions on Circuits and Systems for Video Technology
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Application of biometric algorithms to MPEG-7
CIT'11 Proceedings of the 5th WSEAS international conference on Communications and information technology
The weighted landmark-based algorithm for skull identification
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Some issues of biometrics: technology intelligence, progress and challenges
International Journal of Information Technology and Management
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In the last decade, security aspects such as biometrics have become one of the most central topics for governments as well as researchers, while the availability of more and more advanced technologies at lower costs has made image and video analysis also applicable for this aim. In particular, the 2D image analysis has been widely used in trying to overcome the main drawbacks of the face biometric (pose and illumination). Face is more attractive than most other biometrics, since it is fairly easy to use and well accepted by people, even if not yet robust enough to be used in most practical security applications. One possible way of overcoming this limitation is to work in 3D instead of 2D. But 3D is costly and more difficult to manipulate and then ineffective in authenticating people in most contexts. Hence, to solve this problem, a novel face recognition approach is proposed, using an asymmetric protocol: enrollment in 3D but identification performed from 2D images. So that the goal is to make more robust face recognition while keeping the system practical. To make this 3D/2D approach possible, geometric invariants used in computer vision are introduced within the context of face recognition. Results obtained in terms of identification rate are encouraging.