Typical vs Atypical: Learning Rules of Social Interaction from a Multidisciplinary Perspective Call for Papers


Special Session on 
Typical vs Atypical: Learning Rules of Social Interaction from a Multidisciplinary Perspective
15th IEEE International Conference on Automatic Face and Gesture Recognition 


18-22 May 2020 

Buenos Aires, Argentina 

Important dates

Submission Deadline: 10 December 2019 – midnight PST
Paper notification: 15 January 2020
Final camera-ready papers: 28 February 2020


Humans are a social species and evolution has equipped them with a
unique capacity to navigate the social world. Apart from using spoken
language, nonverbal cues play an essential part in achieving
successful and harmonious social interactions. Yet, only recently have
most psychiatric disorders begun to be conceptualized as “disorders
of social interactions”. Personality disorders, schizophrenia,
anxiety, depression and even neurodevelopmental disorders like autism
are strongly coupled with impairments in the perception,
interpretation and/or production of nonverbal cues. Analysing the
dynamics of typical and atypical social interactions is therefore a
natural and well-fitting means that may help to develop and enhance
automatic psychiatric diagnosis and treatment tools. However, it is a
major challenge to design accessible objective computational
approaches that can tackle the complexity of naturalistic
interpersonal behaviour.

The key aim of this multidisciplinary special session is to unite the
power of computer scientists and social psychologists to discuss
cutting edge research and innovative ideas for investigating
data-driven, supervision-free or explainable methods to model
interpersonal dynamics in both typical and atypical individuals (i.e.,
psychiatric disorders). More specifically, this special session sets
out to put forward opportunities and challenges for learning the rules
of dyadic interactions or small group interactions from large amounts
of video data or other modalities, without extensive use of manual
supervision or prior assumptions, while encouraging the design of
interpretable, safe and reliable techniques that can be adopted
effectively in real-world clinical applications. Topics of interest
include, but not limited to:

    Data-driven approaches to the analysis of nonverbal displays
    expressed within interpersonal context, including facial
    expressions, eye gaze and head movements, body postures and hand
    gestures, audio (e.g., turn taking, vocal outbursts, etc.), and
    the co-modelling of nonverbal and verbal cues;

    Data-driven approaches to the modelling of interpersonal
    coordination such as convergence, synchrony or mimicry;

    Automatic detection of abnormal social behaviour, namely,
    non-conforming patterns in nonverbal interaction;

    Unsupervised/weakly supervised learning of social interaction,
    including representation learning, learning from interpersonal
    context, learning across data modalities, exploiting feature
    correlations, etc.;

    Explainable deep models, ranging from extracting interpretable
    features and visualisation to analysing decision making processes
    and building interactive explanations and human-in-the-loop

    Clinical applications (e.g., autism, depression, anxiety, etc.),
    including defining appropriate qualitative and quantitative
    evaluation methods;

    Novel datasets comprising social interactions among typicals,
    psychiatric disorders, or mixed groups.

       For further details please see

Instructions of paper submission

For instructions of how to submit to the special session please see
https://fg2020.org/instructions-of-paper-submission-for-review/. Once
log in, please click on "create new submission" and choose
"Special Sessions".

We look forward to receiving many exciting contributions! 

With best regards, 
Oya Celiktutan & Alexandra L. Georgescu