Active shape models—their training and application
Computer Vision and Image Understanding
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Action Units for Facial Expression Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Coding Facial Expressions with Gabor Wavelets
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Real Time Facial Expression Recognition with Adaboost
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Recognizing Facial Expression: Machine Learning and Application to Spontaneous Behavior
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Fully Automatic Facial Action Unit Detection and Temporal Analysis
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Facial Expression Recognition Based on Fusion of Multiple Gabor Features
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Face Description with Local Binary Patterns: Application to Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Unified Gradient-Based Approach for Combining ASM into AAM
International Journal of Computer Vision
Face recognition using HOG-EBGM
Pattern Recognition Letters
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph self-organizing maps for cyclic and unbounded graphs
Neurocomputing
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Image and Vision Computing
Patch Alignment for Dimensionality Reduction
IEEE Transactions on Knowledge and Data Engineering
The painful face - Pain expression recognition using active appearance models
Image and Vision Computing
WLD: A Robust Local Image Descriptor
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusing local patterns of gabor magnitude and phase for face recognition
IEEE Transactions on Image Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Harvesting Web Images for Realistic Facial Expression Recognition
DICTA '10 Proceedings of the 2010 International Conference on Digital Image Computing: Techniques and Applications
Feature level analysis for 3D facial expression recognition
Neurocomputing
IEEE Transactions on Image Processing
Face recognition by independent component analysis
IEEE Transactions on Neural Networks
Non-Negative Patch Alignment Framework
IEEE Transactions on Neural Networks
Pairwise constraints based multiview features fusion for scene classification
Pattern Recognition
Learning realistic facial expressions from web images
Pattern Recognition
Hi-index | 0.01 |
Many approaches to facial expression recognition utilize only one type of features at a time. It can be difficult for a single type of features to characterize in a best possible way the variations and complexity of realistic facial expressions. In this paper, we propose a spectral embedding based multi-view dimension reduction method to fuse multiple features for facial expression recognition. Facial expression features extracted from one type of expressions can be assumed to form a manifold embedded in a high dimensional feature space. We construct a neighborhood graph that encodes the structure of the manifold locally. A graph Laplacian matrix is constructed whose spectral decompositions reveal the low dimensional structure of the manifold. In order to obtain discriminative features for classification, we propose to build a neighborhood graph in a supervised manner by utilizing the label information of training data. As a result, multiple features are able to be transformed into a unified low dimensional feature space by combining the Laplacian matrix of each view with the multiview spectral embedding algorithm. A linearization method is utilized to map unseen data to the learned unified subspace. Experiments are conducted on a set of established real-world and benchmark datasets. The experimental results provide a strong support to the effectiveness of the proposed feature fusion framework on realistic facial expressions.