Abstract
Proposed herein are a system and techniques to address issues with insufficient video storage for online video conferences in a manner that provides for reducing the carbon footprint of potentially unused storage. Further, the system and techniques proposed herein may provide for equipping users with a machine-aided understanding of online video conference content by creating machine-digested meeting blueprints, which can help users to avoid tedious/labor intensive, and potentially inefficient downstream tasks. In a multi-recording scenario, the system and techniques proposed herein may be particularly useful to help users understand recording holistically instead of treating each video independently (which can span from minutes to hours). Thus, through the machine-aided techniques and system proposed herein, content from multiple recorded meetings can be reorganized and reconstructed in a manner such that the content can be viewed together.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Jung, Doosan; Sun, Pengfei; and Shao, Qihong, "FACILITATING GREEN AND INTELLIGENT ONLINE VIDEO CONFERENCE STORAGE AND CONSUMPTION USING MULTIMODAL AUGMENTED TEXT-ATTRIBUTED GRAPH (MATAG) TECHNIQUES", Technical Disclosure Commons, (May 15, 2024)
https://www.tdcommons.org/dpubs_series/7011