Game theory, on-line prediction and boosting
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Support vector machines applied to face recognition
Proceedings of the 1998 conference on Advances in neural information processing systems II
Prototyping and Transforming Facial Textures for Perception Research
IEEE Computer Graphics and Applications
Toward Automatic Simulation of Aging Effects on Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICAPR '01 Proceedings of the Second International Conference on Advances in Pattern Recognition
Beyond Eigenfaces: Probabilistic Matching for Face Recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
MORPH: A Longitudinal Image Database of Normal Adult Age-Progression
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Modeling Age Progression in Young Faces
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Modeling Age Progression in Young Faces
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Face Description with Local Binary Patterns: Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational methods for modeling facial aging: A survey
Journal of Visual Languages and Computing
A survey of the effects of aging on biometric identity verification
International Journal of Biometrics
A Compositional and Dynamic Model for Face Aging
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-scale binary patterns for texture analysis
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Face verification across age progression using discriminative methods
IEEE Transactions on Information Forensics and Security
Age transformation for improving face recognition performance
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Revisiting Linear Discriminant Techniques in Gender Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pyramid-based multi-structure local binary pattern for texture classification
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Describable Visual Attributes for Face Verification and Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boosting local binary pattern (LBP)-Based face recognition
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Face Verification Across Age Progression
IEEE Transactions on Image Processing
A Discriminative Model for Age Invariant Face Recognition
IEEE Transactions on Information Forensics and Security - Part 2
Learning multi-scale block local binary patterns for face recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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In this paper we study the task of face verification of age-separated images with the presence of various internal and external factors. We propose a hierarchical local binary pattern (HLBP) feature descriptor for robust face representation across age. The effective representation by HLBP across minimal age, illumination, and expression variations combined with its hierarchical computation provides a discriminative representation of the face image. The proposed face descriptor is combined with an AdaBoost classification framework to model the face verification task as a two-class problem. Experimental results on the FG-NET and MORPH aging datasets indicate that the performance of the proposed framework is robust with respect to images of both adults and children. A detailed empirical analysis on the effects of internal (age gap, gender, and ethnicity) and external (pose, expressions, facial hair, and glasses) factors in the face verification performance is also studied. The results indicate that the verification accuracy reduces as the age gap between the image pair increases. A quantitative comparison on the effects of gender on verification performance by both humans and the proposed machine learning approach is provided. The analysis indicate that the cues aid humans in verifying image pairs with large age gaps, while it aids machines for all age gaps. However, the cues mislead humans in the case of images of children and extra-personal pairs with large age gaps. Our analyses indicate that the pose and expression variations affect the performance, despite training with such variations, while facial hair and glasses act as discriminative cues. A study on the effects of ethnicity indicate that non-linear algorithms have insignificant effect in performance with the use of both generalized and individual ethnicity models when compared with linear algorithms.