Recognition of artificial faces is an intriguing and testing problem and affects important applications in various regions, such as cooperation between human computers and data-oriented activity. Facial expression is the fastest correspondence methods for transmitting data. It is straightforward the outward appearance of an individual by looking at his / her face yet somehow or other with regard to machines it ends up difficult to pass judgment on the outward appearance while using PC devices yet it is not incomprehensible in any way. This not only revealed any individual's affectability or sentiments, but it can also be used to make a judgement on the psychological views, yet again it could not fully understand the perception of human behaviour, the discovery of mental problems and fabricated human expressions. Expressions such as SAD, HAPPY, DISGUST, FEAR, ANGER, NEUTRAL and SURPRISE have been suggested in a broad range of processesThis paper includes implementing face recognition along with facial expression recognition, analyzing recent and past research to extract effective and efficient methods for recognition of facial expression.
Face Expression Recognition, Gabor Filter, Active Appearance Model (AAM), Hidden Markov Model (HMM)
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