Facial expression recognition plays an important role in most social interaction settings . In this context, smiles are considered most easily recognisable but complex facial display . The smile does not always indicate happiness, but also means politeness, sarcasm, rapport, embarrassment, and even frustration . For example, an exhausted worker or a disappointed operator may smile at their customers. It is sometimes very hard to recognise genuine smile properly through open eyes. Thus physiological signals are important in this case as it is not possible to fake or voluntarily control these signals . In this connection, various signal processing and feature (linear and non-linear) extraction methods will be applied to get best relevant features to distinguish between real and posed smiles. It has possible application to understand the behaviour of physically challenged people through their care-givers’ physiological responses.
- To acquire knowledge about physiological signals as well as relevant linear and nonlinear features.
- To find and apply proper signal processing methods to remove noise from the physiological signals.
- To extract relevant features to smiles from the physiological signals.
- To develop a method for distinguishing between real and posed smiles.
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