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ACM Multimedia 2023Grand Challenges

MultiMediate '23: Engagement Estimation and Bodily Behaviour Recognition in Social Interactions

Philipp Müller 0001, Michal Balazia, Tobias Baur 0001, Michael Dietz, Alexander Heimerl, Dominik Schiller, Mohammed Guermal, Dominike Thomas, François Brémond, Jan Alexandersson, Elisabeth André, Andreas Bulling

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3581783.3613851 ↗

摘要

Automatic analysis of human behaviour is a fundamental prerequisite for the creation of machines that can effectively interact with- and support humans in social interactions. In MultiMediate'23, we address two key human social behaviour analysis tasks for the first time in a controlled challenge: engagement estimation and bodily behaviour recognition in social interactions. This paper describes the MultiMediate'23 challenge and presents novel sets of annotations for both tasks. For engagement estimation we collected novel annotations on the NOvice eXpert Interaction (NOXI) database. For bodily behaviour recognition, we annotated test recordings of the MPIIGroupInteraction corpus with the BBSI annotation scheme. In addition, we present baseline results for both challenge tasks.