Inter-ACT: an affective and contextually rich multimodal video corpus for studying interaction with robots

Authors:
Ginevra Castellano;Iolanda Leite;Andre Pereira;Carlos Martinho;Ana Paiva;Peter W. McOwan
Affiliations:
Queen Mary University of London, London, United Kingdom;Instituto Superior Tecnico , Lisbon, Portugal;Instituto Superior Tecnico , Lisbon, Portugal;Instituto Superior Tecnico , Lisbon, Portugal;Instituto Superior Tecnico , Lisbon, Portugal;Queen Mary University of London, London, United Kingdom
Venue:
Proceedings of the international conference on Multimedia
Year:
2010

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Abstract

The Inter-ACT (INTEracting with Robots - Affect Context Task) corpus is an affective and contextually rich multimodal video corpus containing affective expressions of children playing chess with an iCat robot. It contains videos that capture the interaction from different perspectives and includes synchronised contextual information about the game and the behaviour displayed by the robot. The Inter-ACT corpus is mainly intended to be a comprehensive repository of naturalistic and contextualised, task-dependent data for the training and evaluation of an affect recognition system in an educational game scenario. The richness of contextual data that captures the whole human-robot interaction cycle, together with the fact that the corpus was collected in the same interaction scenario of the target application, make the Inter-ACT corpus unique in its genre.