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 ]
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Publications2012 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 [...] [...] 2012 D. Vijayasenan, F. Valente, and H. Bourlard, "Multistream speaker diarization of meetings recordings beyond MFCC and TDOA features," Speech Communication, vol. 54, iss. 1, 2012. full entry
2011 S. H. Yella and F. Valente, "Information Bottleneck Features for HMM/GMM Speaker Diarization of Meetings Recordings," in Proceedings of INTERSPEECH 2011, Florence, 2011. full entry
2011 H. Hung and B. J. A. Krose, "Detecting F-formations as Dominant Sets," in International Conference on Multimodal Interfaces (ICMI), 2011. full entry
2011 A. Veenstra and H. Hung, "Do They Like Me? Using Video Cues to Predict Desires during Speed-dates," in International Conference on Computer Vision Workshop on Socially Intelligent Surveillance Monitoring, 2011. full entry
2011 N. Raiman, H. Hung, and G. Englebienne, "Move, and I will tell you who you are: Detecting deceptive roles in low-quality data," in International Conference on Multimodal Interaction, 2011, pp. 201-204. full entry
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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