Human Emotional Facial Expression Recognition
This work addresses automatic emotion recognition from facial expressions, which is incremental as it builds on existing methods with improvements in feature selection and classification.
The authors tackled facial expression recognition by proposing a model with an Adaboost face detector, manifold learning for feature selection, and a synergetic prototype classifier, achieving favorable effectiveness and reasonable processing time.
An automatic Facial Expression Recognition (FER) model with Adaboost face detector, feature selection based on manifold learning and synergetic prototype based classifier has been proposed. Improved feature selection method and proposed classifier can achieve favorable effectiveness to performance FER in reasonable processing time.