Unobtrusive Sensing of Emotions (USE)
Journal of Ambient Intelligence and Smart Environments
Appearance-based smile intensity estimation by cascaded support vector machines
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Automatic facial expression recognition using statistical-like moments
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Are you friendly or just polite? - analysis of smiles in spontaneous face-to-face interactions
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
The machine knows what you are hiding: an automatic micro-expression recognition system
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Continuous emotion recognition using gabor energy filters
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Unobtrusive Sensing of Emotions (USE)
Journal of Ambient Intelligence and Smart Environments
Regression-based intensity estimation of facial action units
Image and Vision Computing
All smiles: automatic photo enhancement by facial expression analysis
Proceedings of the 9th European Conference on Visual Media Production
Ubiquitous emotion-aware computing
Personal and Ubiquitous Computing
Image and Vision Computing
Learning realistic facial expressions from web images
Pattern Recognition
Enhancing expression recognition in the wild with unlabeled reference data
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Finding happiest moments in a social context
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Emotion recognition in the wild challenge 2013
Proceedings of the 15th ACM on International conference on multimodal interaction
Emotion recognition in the wild challenge (EmotiW) challenge and workshop summary
Proceedings of the 15th ACM on International conference on multimodal interaction
Learning person-specific models for facial expression and action unit recognition
Pattern Recognition Letters
Detecting Facial Expressions for Monitoring Patterns of Emotional Behavior
International Journal of Monitoring and Surveillance Technologies Research
Image and Vision Computing
| Hi-index | 0.14 |
Machine learning approaches have produced some of the highest reported performances for facial expression recognition. However, to date, nearly all automatic facial expression recognition research has focused on optimizing performance on a few databases that were collected under controlled lighting conditions on a relatively small number of subjects. This paper explores whether current machine learning methods can be used to develop an expression recognition system that operates reliably in more realistic conditions. We explore the necessary characteristics of the training data set, image registration, feature representation, and machine learning algorithms. A new database, GENKI, is presented which contains pictures, photographed by the subjects themselves, from thousands of different people in many different real-world imaging conditions. Results suggest that human-level expression recognition accuracy in real-life illumination conditions is achievable with machine learning technology. However, the data sets currently used in the automatic expression recognition literature to evaluate progress may be overly constrained and could potentially lead research into locally optimal algorithmic solutions.