Maia: A Real-time Non-Verbal Chat for Human-AI Interaction
Dragos Costea Alina Marcu Cristina Lazar Marius Leordeanu
Face-to-face communication modeling in computer vision is an area of research
focusing on developing algorithms that can recognize and analyze non-verbal
cues and behaviors during face-to-face interactions. We propose an alternative
to text chats for Human-AI interaction, based on non-verbal visual
communication only, using facial expressions and head movements that mirror,
but also improvise over the human user, to efficiently engage with the users,
and capture their attention in a low-cost and real-time fashion. Our goal is to
track and analyze facial expressions, and other non-verbal cues in real-time,
and use this information to build models that can predict and understand human
behavior. We offer three different complementary approaches, based on
retrieval, statistical, and deep learning techniques. We provide human as well
as automatic evaluations and discuss the advantages and disadvantages of each
direction.