A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
CGIV '04 Proceedings of the International Conference on Computer Graphics, Imaging and Visualization
Neural Networks - Special issue: Emotion and brain
Robust feature detection for facial expression recognition
Journal on Image and Video Processing
Recognition of facial expressions using Gabor wavelets and learning vector quantization
Engineering Applications of Artificial Intelligence
Fuzzy case-based reasoning for facial expression recognition
Fuzzy Sets and Systems
WSEAS Transactions on Computers
Face detection and recognition of natural human emotion using Markov random fields
Personal and Ubiquitous Computing
Personalized Human Emotion Classification Using Genetic Algorithm
VIZ '09 Proceedings of the 2009 Second International Conference in Visualisation
Emotion recognition from facial expressions and its control using fuzzy logic
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm
International Journal of Bio-Inspired Computation
Facial feature model for emotion recognition using fuzzy reasoning
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
International Journal of Computational Science and Engineering
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
Facial action recognition for facial expression analysis from static face images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Face segmentation using skin-color map in videophone applications
IEEE Transactions on Circuits and Systems for Video Technology
Hi-index | 0.00 |
Emotion recognition plays an effective and important role in Human-Computer Interaction (HCI). Recently, various approaches to emotion recognition have been proposed in the literature, but they do not provide a powerful approach to recognize emotions from Partially Occluded Facial Images. In this paper, we propose a new method for Emotion Recognition from Facial Expression using Fuzzy Inference System (FIS). This novel method is even able to recognize emotions from Partially Occluded Facial Images. Moreover, this research describes new algorithms for facial feature extraction that demonstrate satisfactory performance and precision. In addition, one of the main factors that have an important influence on the final precision of fuzzy inference systems is the membership function parameters. Therefore, we use a Genetic Algorithm for parameter-tuning of the membership functions. Experimental results report an average precision rate of 93.96% for Emotion Recognition of six basic emotions, which is so promising.