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26 février 2024

UHBER: Multimodal Data Analysis for Understanding of Human Behaviour, Emotions and their Reasons - Special Session CBMI2024


Catégorie : Conférence internationale


UHBER: Multimodal Data Analysis for Understanding of Human Behaviour, Emotions and their Reasons

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.

https://cbmi2024.org/?page_id=100#UHBER

Please direct correspondence to uhber@cbmi2024.org

Submissions : 6 pages + 1 page of references
https://cbmi2024.org/?page_id=94#submissions


Deadline : 22 march 2024

 

UHBER: Multimodal Data Analysis for Understanding of Human Behaviour, Emotions and their Reasons

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:

Organisers of this special session are:

Please direct correspondence to uhber@cbmi2024.org

https://cbmi2024.org/?page_id=100#UHBER
Submissions : 6 pages + 1 page of references
https://cbmi2024.org/?page_id=94#submissions

Deadline : 22 march 2024

 

 

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