BlendScape: Enabling End-User Customization of Video-Conferencing Environments through Generative AI
This addresses the need for more adaptable video-conferencing tools for distributed collaborators, though it is incremental as it builds on existing AI techniques and prior work on environment design.
The researchers tackled the problem of generic video-conferencing environments by developing BlendScape, a system that uses AI image generation to allow end-users to customize environments, finding in a study with 15 participants that users envisioned its value for collaboration but needed better controls to reduce distractions.
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.