ABSTRACT
The prevalence of virtual meeting software and webcams have normalized holding group meetings both remotely and distributed. However, shifting group meetings virtually with typical computing setups, while convenient, also reduces fluidity of communications. That is, identifying body language of any attendee is complicated from small or lacking on-screen camera views, while distinguishing between multiple attendees’ voices is challenging with lack of spatial audio from commodity speakers and headphones. For my dissertation research, I propose designing and developing intelligent virtual meeting interfaces to narrow communication fluidity gaps between virtual meeting platforms and in-person meeting arrangements. In order to better inform hosts on attendees’ overall body language and attendees on each others’ shared responses, I explore methodologies to automatically recognize users’ physical gestures and intuitively relate them to camera video filters. Therefore, my dissertation goal is to optimally leverage nonverbal communication for improving intelligent user interfaces in virtual meetings.
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Index Terms
- Leveraging Nonverbal Communication for Intelligent Virtual Meeting Interfaces
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