Distinguishing between Real and Posed Smiles from Observers’ Physiological Features

People

Research areas

Description

Facial expression recognition plays an important role in most social interaction settings [1]. In this context, smiles are considered most easily recognisable but complex facial display [2]. The smile does not always indicate happiness, but also means politeness, sarcasm, rapport, embarrassment, and even frustration [3]. 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 [4]. 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.  

Goals

  • 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. 

Background Literature

  1. Hoque, M.E., McDuff, D.J., Picard, R.W.: Exploring temporal patterns in classifying frustrated and delighted smiles. IEEE Transaction on Affective Computing 3(3), 323-334 (2012)
  2. Dibeklioğlu, H., Salah, A.A., Gevers, T.: Recognition of genuine smiles. IEEE Transaction on Multimedia 17(3), 279-294 (2015) 
  3. Frank, M.G., Ekman, P., Friesen, W.V.: Behavioral markers and recognizability of the smile of enjoyment. Journal of Personality and Social Psychology 64(1), 83-93 (1993)
  4. Gong, P., Ma, H. T., Wang, Y.: Emotion recognition based on the multiple physiological signals. IEEE International Conference on Real-time Computing and Robotics, pp. 140- 143. Angkor Wat, Cambodia (2016)

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