The Belief function is a formal framework of increasing interest for imprecise and uncertain data analysis, information fusion and pattern recognition. It has been used in several applications such as image processing, geosciences, medicine, robotics and defence and more recently in the analysis and the recognition of human behaviour such as motion detection, tracking, facial expressions recognition, posture recognition, cued speech gesture recognition, etc.
In this session we would like to invite scientists working in areas related to affective computing, ambient computing, computer vision and machine learning to share their expertise and achievements in the emerging field of automatic analysis of human behaviour using belief functions.
Papers should describe high-quality original research that has direct implications and contributions to human behaviour analysis and recognition. Survey papers are welcome and encouraged.
We are inviting contributions on, but not limited to, the following topics:
· Features segmentation: skin detection, facial features segmentation, hands detection, body-parts detection, silhouette segmentation, etc.
· Face, hands, and body-parts behaviour analysis and interpretation (body posture/action recognition, hand gesture/pose recognition).
· Applications: related, but not limited, to human-machine interaction, multimodal human-machine interaction, context-aware human-machine interaction, surveillance, games, biometry (such as head and body tracking, face/identity recognition, gender recognition, facial expressions recognition, sign language interpretation, etc.)
· Full paper (max. 8 pages) submission: 1st December, 2011
· Notification of acceptance: 20 January, 2012
· Final version: 3 February, 2012
· Conference: 9-11 May, 2012
Submission and reviewing will go through the same submission and review process as regular papers via the session tracks on the online submission system. The Session will have its own track on the online submission system.
Accepted papers will be published by Springer-Verlag in a volume of the series “Advances in Intelligent and Soft Computing” (indexed in ISI Proceedings, DBLP. Ulrich's, EI-Compendex, SCOPUS, Zentralblatt Math, MetaPress, Springerlink).
Zakia Hammal (firstname.lastname@example.org),
Carnegie Mellon University, Pittsburgh, USA