Εργαστήριο Γνώσης και Αβεβαιότητας

Knowledge and Uncertainty Research Laboratory

Recognition of Emotional States in Natural Human-Computer Interaction

[book chapter]


Full reference

R. Cowie, E. Douglas-Cowie, K. Karpouzis, G. Caridakis, M. Wallace, S. Kollias, Recognition of Emotional States in Natural Human-Computer Interaction, in D. Tzovaras (ed.) Multimodal User Interfaces, pp. 119-153, Springer Berlin Heidelberg, 2008



15 known citations

  1. M. Skowron, H. Pirker, S. Rank, G. Paltoglou, J. Ahn and S. Gobron, No peanuts! Affective Cues for the Virtual Bartender, In Proc 24th Florida Artificial Intelligence Research Society Conference, 2011
  2. M. Skowron and G. Paltoglou, Affect Bartender - Affective cues and their application in a conversational agent, 2011 IEEE Workshop on Affective Computational Intelligence (WACI), pp. 1-7, 11-15 April 2011
  3. B.V. Kumar, Face expression recognition and analysis: the state of the art, Internal Report, Columbia University, USA, 2009
  4. J. Prado, C. Simplicio, N.F. Lori and J. Dias, Visuo-Auditory Multimodal Emotional Structure to Improve Human-Robot-Interaction, International Journal of Social Robotics, vol 4, pp. 29-51, 2012
  5. J.Prado, A new probabilistic methodology to support an emotive dialog between a human and a robot, PhD Thesis, University of Coimbra, 2011
  6. G. Valenza, and A. Lanata, and E.P. Scilingo, The Role of Nonlinear Dynamics in Affective Valence and Arousal Recognition, IEEE Transactions on Affective Computing, num. 99, 2011
  7. J. Prado, C. Simplicio and J. Dias, Robot Emotional State through Bayesian Visuo-Auditory Perception, 2nd Doctoral Conference on Computing, Electrical and Industrial Systems, Costa da Caparica, Lisbon, Portugal, 21-23 February 2011
  8. Klaus R. Scherer, Tanja Banziger, Etienne Roesch, A Blueprint for Affective Computing: A sourcebook and manual, Oxford , New York : Oxford University Press, 2010
  9. G. Caridakis, P. Tzouveli, L. Malatesta, A. Raouzaiou, K. Karpouzis, S. Kollias, Affective e-Learning System: Analysis of Learners State, in A. Tzanavari and N. Tsapatsoulis (eds), Affective, Interactive and Cognitive Methods for E-Learning Design: Creating an Optimal Education Experience, pp. 275-294, IGI Global
  10. V. Bettadapura, Face Expression Recognition and Analysis: The State of the Art, Tech Report, Georgia Tech, April 2012.
  11. G. Valenza, A. Lanata and E. P. Scilingo, Oscillations of Heart Rate and Respiration Synchronize During Affective Visual Stimulation, IEEE Transactions on Information Technology in Biomedicine, vol 16, pp. 683-690, 2012
  12. K. Yurtkan and H. Demirel, Entropy-based feature selection for improved 3D facial expression recognition, Signal, Image and Video Processing, vol 8(2), pp. 267-277, 2014
  13. S.I. Anishchenko, V.A. Osinov and D.G. Shaposhnikov, Assessment of human head pose in human-computer interaction, Pattern Recognition and Image Analysis , vol 22(4). pp. 541-545, 2012
  14. G. Valenza and E. P. Scilingo, Autonomic Nervous System Dynamics for Mood and Emotional-State Recognition, Series in BioEngineering, Springer, 2014
  15. K.R. Scherer, T. Banziger and E.B. Roesch, Outlook: integration and future perspectives for affective computing, in K.R. Scherer, T. Banziger and E.B. Roesch (eds) Blueprint for affective computing: a sourcebook, Oxford, New York, Oxford University Press, 2010