Connectionists: CFP "UHBER: Multimodal Data Analysis for Understanding of Human Behaviour, Emotions and their Reasons" - Special Session @ CBMI 2024

[Ioan Marius Bilasco]

Dear colleagues,

This special session addresses the processing of all types of data 
related to understanding of human behaviour, emotion, and their reasons, 
such as current or past context. Understanding human behaviour and 
context may be beneficial for many services both online and in physical 
spaces. For example detecting lack of skills, confusion or other 
negative states may help to adapt online learning programmes, to detect 
a bottleneck in the production line, to recognise poor workplace culture 
etc., or maybe to detect a dangerous spot on a road before any accident 
happens there. Detection of unusual behaviour may help to improve 
security of travellers and safety of dementia sufferers and 
visually/audio impaired individuals, for example, to help them stay away 
from potentially dangerous strangers, e.g., drunk people or football 
fans forming in a big crowd.

In the context of multimedia retrieval, understanding human behaviour 
and emotions could help not only for multimedia indexing, but also to 
derive implicit (i.e., other than intentionally reported) human feedback 
regarding multimedia news, videos, advertisements, navigators, hotels, 
shopping items etc. and improve multimedia retrieval.

Humans are good at understanding other humans, their emotions and 
reasons. For example, when looking at people engaged in different 
activities (sport, driving, working on a computer, working on a 
construction site, using public transport etc.), a human observer can 
understand whether a person is engaged in the task or distracted, 
stopped the recommended video because the video was not interesting, or 
because the person quickly found what he needed in the beginning of the 
video. After observing another human for some time, humans can also 
learn the observed individuals’ tastes, skills and personality traits.

Hence the interest of this session is, how to improve AI understanding 
of the same aspects? The topics include (but are not limited to) the 
following:

  * Use of various sensors for monitoring and understanding human
    behaviour, emotion / mental state / cognition, and context: video,
    audio, infrared, wearables, virtual (e.g., mobile device usage,
    computer usage) sensors etc.
  * Methods for information fusion, including information from various
    heterogeneous sources.
  * Methods to learn human traits and preferences from long term
    observations.
  * Methods to detect human implicit feedback from past and current
    observations.
  * Methods to assess task performance: skills, emotions, confusion,
    engagement in the task and/or context.
  * Methods to detect potential security and safety threats and risks.
  * Methods to adapt behavioural and emotional models to different end
    users and contexts without collecting a lot of labels from each user
    and/or for each context: transfer learning, semi-supervised
    learning, anomaly detection, one-shot learning etc.
  * How to collect data for training AI methods from various sources,
    e.g., internet, open data, field pilots etc.
  * Use of behavioural or emotional data to model humans and adapt
    services either online or in physical spaces.
  * Ethics and privacy issues in modelling human emotions, behaviour,
    context and reasons.

*Organisers of this special session are:*

  * Elena Vildjiounaite, Johanna Kallio, Sari Järvinen, Satu-Marja
    Mäkela, and Sari Järvinen,
    VTT Technical Research Center of Finland, Finland.
  * Benjamin Allaert, IMT-Nord_Europe, France.
  * Ioan Marious Bilasco, University of Lille, France.
  * Franziska Schmalfuss, IAV GmbH, Germany.

Please direct correspondence to uhber at cbmi2024.org

*Paper submission:* 6 pages + 1 page of references
*Deadline:* 22 march 2024
https://cbmi2024.org/?page_id=94#submissions

Best regards


--
Ioan Marius BILASCO
https://pro.univ-lille.fr/marius-bilasco/
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