Abstract

We present a novel scheme for facial expression recognition from facial features using Mamdani-type fuzzy system. Facial expression recognition is of prime importance in human-computer interaction systems (HCI). HCI has gained importance in web information systems and e-commerce and certainly has the potential to reshape the IT landscape towards value driven perspectives. We present a novel algorithm for facial region extraction from static image. These extracted facial regions are used for facial feature extraction. Facial features are fed to a Mamdani-type fuzzy rule based system for facial expression recognition. Linguistic models employed for facial features provide an additional insight into how the rules combine to form the ultimate expression output. Another distinct feature of our system is the membership function model of expression output which is based on different psychological studies and surveys. The validation of the model is further supported by the high expression recognition percentage.

Keywords:
Facial expression Computer science Fuzzy logic Feature extraction Feature (linguistics) Artificial intelligence Three-dimensional face recognition Pattern recognition (psychology) Facial recognition system Expression (computer science) Face hallucination Computer vision Speech recognition Face detection

Metrics

4
Cited By
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FWCI (Field Weighted Citation Impact)
20
Refs
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Citation Normalized Percentile
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Citation History

Topics

Face and Expression Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Emotion and Mood Recognition
Social Sciences →  Psychology →  Experimental and Cognitive Psychology
Fuzzy Logic and Control Systems
Physical Sciences →  Computer Science →  Artificial Intelligence
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