BlendScape: Enabling Unified and Personalized Video-Conferencing Environments through Generative AI
CoRR(2024)
摘要
Today's video-conferencing tools support a rich range of professional and
social activities, but their generic, grid-based environments cannot be easily
adapted to meet the varying needs of distributed collaborators. To enable
end-user customization, we developed BlendScape, a system for meeting
participants to compose video-conferencing environments tailored to their
collaboration context by leveraging AI image generation techniques. BlendScape
supports flexible representations of task spaces by blending users' physical or
virtual backgrounds into unified environments and implements multimodal
interaction techniques to steer the generation. Through an evaluation with 15
end-users, we investigated their customization preferences for work and social
scenarios. Participants could rapidly express their design intentions with
BlendScape and envisioned using the system to structure collaboration in future
meetings, but experienced challenges with preventing distracting elements. We
implement scenarios to demonstrate BlendScape's expressiveness in supporting
distributed collaboration techniques from prior work and propose composition
techniques to improve the quality of environments.
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