Introduction to the theory of neural computation
Introduction to the theory of neural computation
Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
International Journal of Man-Machine Studies - Special issue: symbolic problem solving in noisy and novel task environments
C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
Machine Learning - Special issue on learning with probabilistic representations
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
Machine Learning
Machine Learning
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
Coding Facial Expressions with Gabor Wavelets
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Comprehensive Database for Facial Expression Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Robust Computer Vision: Theory and Applications
Robust Computer Vision: Theory and Applications
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
IEEE Transactions on Pattern Analysis and Machine Intelligence
A system for induction of oblique decision trees
Journal of Artificial Intelligence Research
Editorial: The age of human computer interaction
Image and Vision Computing
Affective feedback: an investigation into the role of emotions in the information seeking process
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Integrated Computer-Aided Engineering
Pose-Invariant Facial Expression Recognition Using Variable-Intensity Templates
International Journal of Computer Vision
A comparison of general vs personalised affective models for the prediction of topical relevance
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Spatiotemporal-boosted DCT features for head and face gesture analysis
HBU'10 Proceedings of the First international conference on Human behavior understanding
Robust classification of face and head gestures in video
Image and Vision Computing
Modeling of operators' emotion and task performance in a virtual driving environment
International Journal of Human-Computer Studies
An application of interactive game for facial expression of the autisms
Edutainment'11 Proceedings of the 6th international conference on E-learning and games, edutainment technologies
Proceedings of the 2012 Joint International Conference on Human-Centered Computer Environments
3D human face description: landmarks measures and geometrical features
Image and Vision Computing
Recognition of 3D facial expression dynamics
Image and Vision Computing
Facial expression recognition using tracked facial actions: Classifier performance analysis
Engineering Applications of Artificial Intelligence
Spatiotemporal features for effective facial expression recognition
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Facial expression recognition based on anatomy
Computer Vision and Image Understanding
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There is a growing trend toward emotional intelligence in human-computer interaction paradigms. In order to react appropriately to a human, the computer would need to have some perception of the emotional state of the human. We assert that the most informative channel for machine perception of emotions is through facial expressions in video. One current difficulty in evaluating automatic emotion detection is that there are currently no international databases which are based on authentic emotions. The current facial expression databases contain facial expressions which are not naturally linked to the emotional state of the test subject. Our contributions in this work are twofold: first, we create the first authentic facial expression database where the test subjects are showing the natural facial expressions based upon their emotional state. Second, we evaluate the several promising machine learning algorithms for emotion detection which include techniques such as Bayesian networks, SVMs, and decision trees.