A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coding, Analysis, Interpretation, and Recognition of Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
International Journal of Computer Vision
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
Subtly Different Facial Expression Recognition and Expression Intensity Estimation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Connected Vibrations: A Modal Analysis Approach for Non-Rigid Motion Tracking
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Feature-Point Tracking by Optical Flow Discriminates Subtle Differences in Facial Expression
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
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
Parametric models for facial features segmentation
Signal Processing
Extraction and tracking of the eyelids
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Belief theory applied to facial expressions classification
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Facial expression recognition based on the belief theory: comparison with different classifiers
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Facial expression recognition from line-based caricatures
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Accurate and quasi-automatic lip tracking
IEEE Transactions on Circuits and Systems for Video Technology
Human expression recognition from motion using a radial basis function network architecture
IEEE Transactions on Neural Networks
Multi-camera people tracking using evidential filters
International Journal of Approximate Reasoning
Shape from silhouette using Dempster-Shafer theory
Pattern Recognition
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
International Journal of Approximate Reasoning
Visual affect recognition
Approximate reasoning and finite state machines to the detection of actions in video sequences
International Journal of Approximate Reasoning
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Pain monitoring: A dynamic and context-sensitive system
Pattern Recognition
A skin detection approach based on the Dempster--Shafer theory of evidence
International Journal of Approximate Reasoning
Theory of evidence for face detection and tracking
International Journal of Approximate Reasoning
Spontaneous pain expression recognition in video sequences
VoCS'08 Proceedings of the 2008 international conference on Visions of Computer Science: BCS International Academic Conference
Bee royalty offspring algorithm for improvement of facial expressions classification model
International Journal of Bio-Inspired Computation
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A method for the classification of facial expressions from the analysis of facial deformations is presented. This classification process is based on the transferable belief model (TBM) framework. Facial expressions are related to the six universal emotions, namely Joy, Surprise, Disgust, Sadness, Anger, Fear, as well as Neutral. The proposed classifier relies on data coming from a contour segmentation technique, which extracts an expression skeleton of facial features (mouth, eyes and eyebrows) and derives simple distance coefficients from every face image of a video sequence. The characteristic distances are fed to a rule-based decision system that relies on the TBM and data fusion in order to assign a facial expression to every face image. In the proposed work, we first demonstrate the feasibility of facial expression classification with simple data (only five facial distances are considered). We also demonstrate the efficiency of TBM for the purpose of emotion classification. The TBM based classifier was compared with a Bayesian classifier working on the same data. Both classifiers were tested on three different databases.