CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
An experimental comparison of gender classification methods
Pattern Recognition Letters
Facial Gender Classification Using Shape from Shading and Weighted Principal Geodesic Analysis
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
A study on gait-based gender classification
IEEE Transactions on Image Processing
Increasing the Robustness of 2D Active Appearance Models for Real-World Applications
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Generalized multi-ethnic face age-estimation
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Facial gender classification using shape-from-shading
Image and Vision Computing
A review of active appearance models
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Automatic facial expression recognition using boosted discriminatory classifiers
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Gender classification in uncontrolled settings using additive logistic models
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Supervised relevance maps for increasing the distinctiveness of facial images
Pattern Recognition
Bag of soft biometrics for person identification
Multimedia Tools and Applications
Gender discriminating models from facial surface normals
Pattern Recognition
Facial expression recognition for learning status analysis
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: users and applications - Volume Part IV
Gender identification using feature patch-based bayesian classifier
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
Gender classification of human face images based on adaptive features and support vector machines
Optical Memory and Neural Networks
| Hi-index | 0.00 |
This paper presents an approach to recognising the gender and expression of face images by means of Active Appearance Models (AAM). Features extracted by a trained AAM are used to construct Support Vector Machine (SVM) classifiers for 4 elementary emotional states (happy, angry, sad, neutral). These classifiers are arranged into a cascade structure in order to optimise overall recognition performance. Furthermore, it is shown how performance can be further improved by first classifying the gender of the face images using an SVM trained in a similar manner. Both gender-specific expression classification and expression-specific gender classification cascades are considered, with the former yielding better recognition performance. We conclude that there are gender-specific differences in the appearance of facial expressions that can be exploited for automated recognition, and that cascades are an efficient and effective way of performing multi-class recognition of facial expressions.