Age classification from facial images
Computer Vision and Image Understanding
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Gender with Support Faces
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
Gender and Ethnic Classification of Face Images
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
The CMU Pose, Illumination, and Expression (PIE) Database
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Boosting Nested Cascade Detector for Multi-View Face Detection
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Jensen-Shannon Boosting Learning for Object Recognition
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
LUT-based Adaboost for gender classification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Ethnicity estimation with facial images
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Multimodal facial gender and ethnicity identification
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Real time facial expression recognition using local binary patterns and linear programming
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Computational methods for modeling facial aging: A survey
Journal of Visual Languages and Computing
Pixelwise Local Binary Pattern Models of Faces Using Kernel Density Estimation
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Face Age Classification on Consumer Images with Gabor Feature and Fuzzy LDA Method
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Face Gender Classification on Consumer Images in a Multiethnic Environment
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Ethnicity- and Gender-based Subject Retrieval Using 3-D Face-Recognition Techniques
International Journal of Computer Vision
Learning local features for age estimation on real-life faces
Proceedings of the 1st ACM international workshop on Multimodal pervasive video analysis
Gait-based human age estimation
IEEE Transactions on Information Forensics and Security
Combining contrast information and local binary patterns for gender classification
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Learning gabor features for facial age estimation
CCBR'11 Proceedings of the 6th Chinese conference on Biometric recognition
Gender from body: a biologically-inspired approach with manifold learning
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Image and Vision Computing
Ethnicity classification based on a hierarchical fusion
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
| Hi-index | 0.00 |
LBP (Local Binary Pattern) as an image operator is used to extract LBPH (LBP histogram) features for texture description. In this paper, we present a novel method to use LBPH feature in ordinary binary classification problem. Given a restricted local patch, the Chi square distance between the extracted LBPH and a reference histogram is used as a measure of confidence belonging to the reference class, and an optimal reference histogram is obtained by iteratively optimization; real AdaBoost algorithm is used to learn a sequence of best local features iteratively and combine them into a strong classifier. The experiments on age, gender and ethnicity classification demonstrate its effectiveness.