2012
L. van der Maaten and E. Hendriks, "Action Unit Classification using Active Appearance Models and Conditional Random Fields," Cognitive Processing, 2012. full entry
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Publications2011 I. Poggi and F. DÉrrico, "Social signals: A psychological perspective." . Springer Verlag’s Advances in Pattern Recognition series, 2011, pp. 185-225. full entry [ download ]
2011 I. Poggi, F. DÉrrico, and L. Vincze, "Discrediting moves in political debate," in Proceedings of Second International Workshop on User Models for Motivational Systems: the affective and the rational routes to persuasion, 2011, pp. 84-99. full entry [ download ]
2011 I. Poggi and F. DÉrrico, "Types of pride and their expression," in Analysis of Verbal and Nonverbal Communication and Enactment: The Processing Issues, 2011, pp. 445-459. full entry [ download ]
2011 L. Vincze and I. Poggi, "Communicative Functions of Eye Closing Behaviours," in Analysis of Verbal and Nonverbal Communication and Enactment: The Processing Issues, 2011, pp. 401-416. full entry
2012 X. Sun, K. Truong, A. Nijholt, and M. Pantic, "Automatic Visual Mimicry Expression Analysis in Interpersonal Interaction," in Proc. IEEE Int’l Conf. Computer Vision and Pattern Recognition (CVPR-W’11), Workshop on CVPR for Human Behaviour Analysis, 2012, pp. 40-46. full entry [ download ]
2012 M. F. Valstar and M. Pantic, "Fully Automatic Recognition of the Temporal Phases of Facial Actions," IEEE Transactions on Systems, Man and Cybernetics – Part B, vol. 42, iss. 1, pp. 28-43, 2012. full entry
2012 M. Soleymani, T. Pun, and M. Pantic, "Multi-Modal Emotion Recognition in Response to Videos," IEEE Transactions on Affective Computing, accepted for publication, 2012. full entry [ download ]
The School of Computer Science (CS) at the University of Nottingham offers an exciting opportunity for a PhD studentship in the field of Automatic Human Behaviour Understanding, applying and developing Computer Vision and Machine Learning techniques to aid future Human Computer Interaction (HCI). The PhD post is intended to complement and extend the existing research [...] [...]
iBUG's TAUD (Temporal-based Action Unit Detection) is the implementation of our LPQ-TOP-based AU detector. It is developed as a WIN32 executable. It includes trained models for the following AUs: ... |
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