Facial expressional image synthesis controlled by emotional parameters
Pattern Recognition Letters
Expression recognition using fuzzy spatio-temporal modeling
Pattern Recognition
Illumination-robust face recognition using ridge regressive bilinear models
Pattern Recognition Letters
Expression-invariant face recognition by facial expression transformations
Pattern Recognition Letters
Modelling human perception of static facial expressions
Image and Vision Computing
Person-similarity weighted feature for expression recognition
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Visual affect recognition
Discrete choice models for static facial expression recognition
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Tensor rank one differential graph preserving analysis for facial expression recognition
Image and Vision Computing
| Hi-index | 0.01 |
Facial expression interpretation, recognition and analysis is a key issue in visual communication and man to machine interaction. In this paper, we address the issues of facial expression recognition and synthesis and compare the proposed bilinear factorization based representations with previously investigated methods such as linear discriminant analysis and linear regression. We conclude that bilinear factorization outperforms these techniques in terms of correct recognition rates and synthesis photorealism especially when the number of training samples is restrained.