Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
What Is the Set of Images of an Object Under All Possible Illumination Conditions?
International Journal of Computer Vision
Independent component analysis: theory and applications
Independent component analysis: theory and applications
Robust recognition using eigenimages
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition Using Line Edge Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstruction of Partially Damaged Face Images Based on a Morphable Face Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Smiling Faces are Better for Face Recognition
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Computer Vision and Image Understanding
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Journal of Cognitive Neuroscience
Recognizing expression variant faces from a single sample image per class
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Face recognition in non-uniform illumination conditions using lighting normalization and SVM
CEA'07 Proceedings of the 2007 annual Conference on International Conference on Computer Engineering and Applications
Classification of face images using local iterated function systems
Machine Vision and Applications
Reliable face recognition using adaptive and robust correlation filters
Computer Vision and Image Understanding
Face Recognition with VG-RAM Weightless Neural Networks
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
3D Multimedia Data Search System Based on Stochastic ARG Matching Method
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Bayesian Face Recognition Based on Markov Random Field Modeling
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Why Is Facial Occlusion a Challenging Problem?
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Face recognition under occlusions and variant expressions with partial similarity
IEEE Transactions on Information Forensics and Security
Face alignment by minimizing the closest classification distance
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
The complete gabor-fisher classifier for robust face recognition
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Three-Dimensional Occlusion Detection and Restoration of Partially Occluded Faces
Journal of Mathematical Imaging and Vision
Computer Vision and Image Understanding
Learning kernel subspace classifier
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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In this paper, we propose a novel line feature-based face recognition algorithm. A face is represented by the Face-ARG model, where all the geometric quantities and the structural information are encoded in an Attributed Relational Graph (ARG) structure, then the partial ARG matching is done for matching Face-ARG's. Experimental results demonstrate that the proposed algorithm is quite robust to various facial expression changes, varying illumination conditions and occlusion, even when a single sample per person is given.