Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Matrix computations (3rd ed.)
Error Probability in Decision Functions for Character Recognition
Journal of the ACM (JACM)
Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Robust Real-Time Face Detection
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Supervised dimensionality reduction using mixture models
ICML '05 Proceedings of the 22nd international conference on Machine learning
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pedestrian Detection via Classification on Riemannian Manifolds
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pose-Invariant Facial Expression Recognition Using Variable-Intensity Templates
International Journal of Computer Vision
Region covariance: a fast descriptor for detection and classification
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
3D shape estimation in video sequences provides high precision evaluation of facial expressions
Image and Vision Computing
Describing video contents in natural language
HYBRID '12 Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data
Multi-view facial expression recognition analysis with generic sparse coding feature
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
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Emotion recognition from facial images is a very active research topic in human computer interaction (HCI). However, most of the previous approaches only focus on the frontal or nearly frontal view facial images. In contrast to the frontal/nearly-frontal view images, emotion recognition from non-frontal view or even arbitrary view facial images is much more difficult yet of more practical utility. To handle the emotion recognition problem from arbitrary view facial images, in this paper we propose a novel method based on the regional covariance matrix (RCM) representation of facial images. We also develop a new discriminant analysis theory, aiming at reducing the dimensionality of the facial feature vectors while preserving the most discriminative information, by minimizing an estimated multiclass Bayes error derived under the Gaussian mixture model (GMM). We further propose an efficient algorithm to solve the optimal discriminant vectors of the proposed discriminant analysis method. We render thousands of multi-view 2D facial images from the BU-3DFE database and conduct extensive experiments on the generated database to demonstrate the effectiveness of the proposed method. It is worth noting that our method does not require face alignment or facial landmark points localization, making it very attractive.