Songqing Chen, Professor, Computer Science, Volgenau School of Engineering, and his collaborators are set to begin a project aimed at improving users' ability to share 360-degree videos.
360-degree video allows users to explore a recorded scene from any angle relative to the camera position.
This format affords users added flexibility, but widespread adoption has slowed due to the large amounts of resources required by the format.
Via this project, Chen and his collaborators will develop methods to improve efficiency at each stage of the 360-degree video sharing path, from video capture on the sender's side to consumption on the receiver's side.
The researchers will address the challenges of this format via four research thrusts.
First, they will explore approaches for generating high-quality frames during real-time stitching of multiple videos captured using commodity lenses.
Second, they will investigate mechanisms to spatially adapt content to be uploaded based on the available bandwidth.
Third, they will optimize the fine-grained representation of omnidirectional content to achieve high projection efficiency and view efficiency.
Finally, they will use edge computing techniques to optimize the look-ahead window size on the receiver side to allow bandwidth-efficient content downloading. Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth.
The researchers expect that the techniques developed during the course of the project will allow users to enjoy more efficient 360-degree video streaming applications. They also anticipate the techniques will have applications in future generations of virtual reality (VR) technologies.
Chen and his collaborators will produce publications, code, data, and other research artifacts as part of this work. They will make these items publicly available through two URLs: http://www.cs.gmu.edu/~sqchen/ and http://www.cs.binghamton.edu/~yaoliu/ during the course of the project and the artifacts will remain available for at least five years after completion of the project. The code will be open sourced and will also be made available via a code hosting website (e.g., GitHub).
Chen will receive $249,910 from the National Science Foundation for this project. Funding will begin in October 2020 and will conclude in late September 2023.
###