BlendScape: Enabling End-User Customization of Video-Conferencing Environments through Generative AI

Abstract

Today's video-conferencing tools support a rich range of professional and social activities, but their generic meeting environments cannot be dynamically adapted to align with distributed collaborators' needs. To enable end-user customization, we developed BlendScape, a rendering and composition system for video-conferencing participants to tailor environments to their meeting context by leveraging AI image generation techniques. BlendScape supports flexible representations of task spaces by blending users' physical or digital backgrounds into unified environments and implements multimodal interaction techniques to steer the generation. Through an exploratory study with 15 end-users, we investigated whether and how they would find value in using generative AI to customize video-conferencing environments. Participants envisioned using a system like BlendScape to facilitate collaborative activities in the future, but required further controls to mitigate distracting or unrealistic visual elements. We implemented scenarios to demonstrate BlendScape's expressiveness for supporting environment design strategies from prior work and propose composition techniques to improve the quality of environments.