[Amdnl] CFP: Special Session on recognition Of Affect Signals from physiologIcal data for Social robots (OASIS 2014) @ PhyCS'14 (Deadline extended to Nov. 6)

[Iolanda Leite]

***Special Session on recognition Of Affect Signals from physiologIcal data
for Social robots (OASIS 2014)***

www.phycs.org/OASIS.aspx

In conjunction with the International Conference on Physiological Computing
Systems (PhyCS 2014) and in Cooperation with FP7 EU-project EMOTE.

7 - 9 January, 2014 - Lisbon, Portugal

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Scope:

With the recent advances in biosensor technology, small, wireless and
inexpensive sensors are becoming increasingly more popular, as users can
wear these sensors while performing a large set of activities without
becoming intrusive. These devices can measure, for example, arousal through
skin conductance, a form of electrodermal activity linked to states of
excitement, attention, anxiety or cognitive load. Socially and affect-aware
robots that can capture some of these states from the user are considered
more effective in engaging users for longer periods of time. For these
reasons, research on physiological signals has been attracting the
attention of researchers in the Human-Robot Interaction (HRI) community.

The focus of the session is on how to apply physiological computing in
order to make robots more interactive, socially aware and empathic towards
users. By addressing these challenges, we expect to attract researchers
from the areas of Human-Robot Interaction, Affective Computing, Multimodal
Behavioural Perception and Social Signal Processing. The main expected
outcomes are the identification and discussion of the most relevant
challenges, issues and opportunities of using this technology in HRI
scenarios. We expect to promote closer interaction among researchers from
different communities, and to provide a forum in which researchers can
share and discus their main findings in this area.

Topics of interest include:

- Affect and behaviour recognition using physiological data
- Multimodal human affect and social behaviour recognition
- Applications for physiological data in human-robot and human-computer
interaction
- Techniques for pattern recognition and social signal processing
- Methodologies for using physiological data in HRI and HCI evaluations
- Data collection in real-world environments

Important dates:

Paper Submission: November 6, 2013
Authors Notification: November 20, 2013
Camera Ready and Registration: December 2, 2013

Organizing Committee:

Ginevra Castellano, University of Birmingham, UK
Iolanda Leite, Yale University, USA
Ana Paiva, INESC-ID and IST, Technical University of Lisbon, Portugal

Program Committee:

Patrícia Arriaga, ISCTE-IUL, Portugal
Christian Becker-Asano, Albert-Ludwigs-Universität Freiburg, Germany
Sidney D’Mello, University of Notre Dame,USA
Hatice Gunes, Queen Mary University of London, UK
Rui Henriques, Instituto Superior Técnico, Portugal
Ehsan Hoque, MIT Media Lab, USA
Arvid Kappas, Jacobs University Bremen, Germany
Dennis Küster, Jacobs University Bremen, Germany
Laurel Riek, University of Notre Dame, USA
Astrid Rosenthal-von der Pütten, University of Duisburg-Essen, Germany
Mohammad Soleymani, Imperial College London, UK
Adriana Tapus, ENSTA-ParisTech, France
Georgios N. Yannakakis, IT University of Copenhagen


-- 
Iolanda Leite
Postdoctoral Associate
Socially Assistive Robotics: An NSF Expedition in Computing
Department of Computer Science
Yale University
robotshelpingkids.com • scazlab.yale.edu •
iolandaleite.com<http://iolandaleite.wordpress.com>
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