NOVICOM

Automatic Analysis of Group Conversations via Visual Cues in Non-Verbal Communication

 Coordinatore FONDATION DE L'INSTITUT DE RECHERCHE IDIAP 

 Organization address address: RUE MARCONI 19
city: MARTIGNY
postcode: 1920

contact info
Titolo: Dr.
Nome: François
Cognome: Foglia
Email: send email
Telefono: +41 27 721 77 50
Fax: +41 27 721 77 12

 Nazionalità Coordinatore Switzerland [CH]
 Totale costo 183˙266 €
 EC contributo 183˙266 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-IEF-2008
 Funding Scheme MC-IEF
 Anno di inizio 2009
 Periodo (anno-mese-giorno) 2009-06-01   -   2011-10-14

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    FONDATION DE L'INSTITUT DE RECHERCHE IDIAP

 Organization address address: RUE MARCONI 19
city: MARTIGNY
postcode: 1920

contact info
Titolo: Dr.
Nome: François
Cognome: Foglia
Email: send email
Telefono: +41 27 721 77 50
Fax: +41 27 721 77 12

CH (MARTIGNY) coordinator 183˙266.34

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 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

interaction    visual    interactions    gestures    cues    behavior    human    nonverbal    computational    automatic    social    group    computer    communication    concentrate   

 Obiettivo del progetto (Objective)

'Computational analysis of social interaction is an emerging field of research in several communities such as human computer interaction, machine learning, speech and language processing, and computer vision. Social psychologists have researched the dimensions of social interaction for decades, finding out that nonverbal cues strongly determine human behavior and communication. One of the ultimate aims in computational analysis is to develop computational systems that can automatically recognize, discover, or predict human behavior via sensing devices such as cameras and microphones. The scientific objective of this proposal is to develop new and principled computational methods to detect and analyze visual nonverbal cues for the automatic analysis of social interaction in small group face-to-face conversations. Specifically, we will concentrate on hand gestures, head gestures and body posture. As nonverbal communication in social interactions does not only include visual cues but also the aural ones, the automatic analysis of interactions requires the use of both cues in modeling and recognition. Hence, our specific objectives are (1) the automatic detection and analysis of visual nonverbal communication cues, and (2) the multimodal integration of audio and visual nonverbal cues. We will concentrate on a selected number of key research tasks in social interaction analysis including, among others, the automatic estimation of dominance in a group conversation, and the level of interest of the members of the group during their interaction.'

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