SunFA - An open-source application for behavior analysis in online video-conferencing

ABSTRACT

Video-conferencing applications are becoming increasingly popular, especially with the remote working trend after COVID-19. The benefits of meeting online cannot be denied;however, this is still quite limited. In particular, it is essential to monitor and analyze participants' behavior. In this paper, we proposed SunFA - an open-source participants analysis tool for video-conferencing based on face analysis and virtual camera technology. The advantage of our system is that it is compatible with almost available video conferencing applications, such as Google Meet, Skype, Microsoft Teams, Zoom, Slack, etc. Furthermore, we packaged this software as a desktop application for Windows operating system to make it easy to install. The memory usage and execution time evaluation ensure the real-time and resource-saving of a video-conferencing application. We open-source our entire source code and solutions at https//github.com/sun-asterisk-research/sun-fa © 2022 IEEE.