An analysis of facial expression recognition under partial facial image occlusion
Image and Vision Computing
Emotionally aware automated portrait painting
Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts
Pose-Invariant Facial Expression Recognition Using Variable-Intensity Templates
International Journal of Computer Vision
Emotional intensity-based facial expression cloning for low polygonal applications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Novel multiclass classifiers based on the minimization of the within-class variance
IEEE Transactions on Neural Networks
Real-time 2D+3D facial action and expression recognition
Pattern Recognition
Adjusted pixel features for robust facial component classification
Image and Vision Computing
A model-based facial expression recognition algorithm using principal components analysis
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Multi-feature fusion in advanced robotics applications
Proceedings of the 7th International Conference on Frontiers of Information Technology
Facial expression recognition on multiple manifolds
Pattern Recognition
Expert Systems with Applications: An International Journal
Facial expression classification based on local spatiotemporal edge and texture descriptors
Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research
Facial expression recognition using facial features andmanifold learning
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Analysis of landmarks in recognition of face expressions
Pattern Recognition and Image Analysis
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
On the simultaneous recognition of identity and expression from BU-3DFE datasets
Pattern Recognition Letters
Higher rank Support Tensor Machines for visual recognition
Pattern Recognition
Towards the improvement of self-service systems via emotional virtual agents
BCS-HCI '12 Proceedings of the 26th Annual BCS Interaction Specialist Group Conference on People and Computers
Recognition of 3D facial expression dynamics
Image and Vision Computing
Facial expression recognition using geometric and appearance features
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
LSTM-Modeling of continuous emotions in an audiovisual affect recognition framework
Image and Vision Computing
Using robust dispersion estimation in support vector machines
Pattern Recognition
Emotion recognition using facial and audio features
Proceedings of the 15th ACM on International conference on multimodal interaction
Facial expression recognition in dynamic sequences: An integrated approach
Pattern Recognition
Dynamic facial expression analysis based on extended spatio-temporal histogram of oriented gradients
International Journal of Biometrics
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In this paper, two novel methods for facial expression recognition in facial image sequences are presented. The user has to manually place some of Candide grid nodes to face landmarks depicted at the first frame of the image sequence under examination. The grid-tracking and deformation system used, based on deformable models, tracks the grid in consecutive video frames over time, as the facial expression evolves, until the frame that corresponds to the greatest facial expression intensity. The geometrical displacement of certain selected Candide nodes, defined as the difference of the node coordinates between the first and the greatest facial expression intensity frame, is used as an input to a novel multiclass Support Vector Machine (SVM) system of classifiers that are used to recognize either the six basic facial expressions or a set of chosen Facial Action Units (FAUs). The results on the Cohn-Kanade database show a recognition accuracy of 99.7% for facial expression recognition using the proposed multiclass SVMs and 95.1% for facial expression recognition based on FAU detection