C4.5: programs for machine learning
C4.5: programs for machine learning
Active shape models—their training and application
Computer Vision and Image Understanding
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Analysis of Facial Expressions: The State of the Art
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
Machine Learning
Comprehensive Database for Facial Expression Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
Robust Real-Time Face Detection
International Journal of Computer Vision
Active and Dynamic Information Fusion for Facial Expression Understanding from Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Geometry-Driven Photorealistic Facial Expression Synthesis
IEEE Transactions on Visualization and Computer Graphics
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships
IEEE Transactions on Pattern Analysis and Machine Intelligence
How to distinguish posed from spontaneous smiles using geometric features
Proceedings of the 9th international conference on Multimodal interfaces
Automatic feature localisation with constrained local models
Pattern Recognition
Lipless Tracking and Emotion Estimation
SITIS '07 Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Approach to Fuzzy-Rough Nearest Neighbour Classification
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Image and Vision Computing
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing Accurate Correspondences across Groups of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial feature model for emotion recognition using fuzzy reasoning
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Facial action recognition for facial expression analysis from static face images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
Dynamic Facial Expression Analysis and Synthesis With MPEG-4 Facial Animation Parameters
IEEE Transactions on Circuits and Systems for Video Technology
Fully Automatic Recognition of the Temporal Phases of Facial Actions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Evaluation of cluster identification performance for different PCP variants
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Visualization of time-series data in parameter space for understanding facial dynamics
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
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Automatic facial expression analysis aims to analyse human facial expressions and classify them into discrete categories. Methods based on existing work are reliant on extracting information from video sequences and employ either some form of subjective thresholding of dynamic information or attempt to identify the particular individual frames in which the expected behaviour occurs. These methods are inefficient as they require either additional subjective information, tedious manual work or fail to take advantage of the information contained in the dynamic signature from facial movements for the task of expression recognition. In this paper, a novel framework is proposed for automatic facial expression analysis which extracts salient information from video sequences but does not rely on any subjective preprocessing or additional user-supplied information to select frames with peak expressions. The experimental framework demonstrates that the proposed method outperforms static expression recognition systems in terms of recognition rate. The approach does not rely on action units (AUs), and therefore, eliminates errors which are otherwise propagated to the final result due to incorrect initial identification of AUs. The proposed framework explores a parametric space of over 300 dimensions and is tested with six state-of-the-art machine learning techniques. Such robust and extensive experimentation provides an important foundation for the assessment of the performance for future work. A further contribution of the paper is offered in the form of a user study. This was conducted in order to investigate the correlation between human cognitive systems and the proposed framework for the understanding of human emotion classification and the reliability of public databases.