To this end, a deep learning based 360 degree video codec will be built to distill the spatiotemporal characteristics of video features and optimize both compression ratio and analytics accuracy. Second, an adaptive 360 degree video bitrate streaming system will be designed to ensure continuous delivery of full 360 degree video frames by prioritizing regions of interest preferred by machines. Third, a 360 degree video recovery scheme will be developed to restore noisy and delayed video data while considering the time constraints in the online analytics.
People
- PI Zhisheng Yan
- External Collaborator Klara Nahrstedt, UIUC
- Students Anh Phan Nguyen, Bo Chen, Taslim Murad
Publications
- LiFteR: Unleash Learned Codecs in Video Streaming with Loose Frame Referencing Bo Chen, Zhisheng Yan, Yinjie Zhang, Zhe Yang, and Klara Nahrstedt USENIX NSDI (USENIX Symposium on Networked Systems Design and Implementation), April 2024. [PDF]
- Vesper: Learning to Manage Uncertainty in Video Streaming Bo Chen, Mingyuan Wu, Hongpeng Guo, Zhisheng Yan, and Klara Nahrstedt ACM MMSys (ACM International Conference on Multimedia Systems), April 2024. [PDF]
- Context-aware Optimization for Bandwidth-Efficient Image Analytics Offloading Bo Chen, Zhisheng Yan, and Klara Nahrstedt ACM TOMM (ACM Transactions on Multimedia Computing, Communications, and Applications), December 2023. [PDF]
- Enhancing 360 Video Streaming through Salient Content in Head-Mounted Displays Anh Nguyen and Zhisheng Yan Sensors, April 2023. [PDF]
- Context-aware Image Compression Optimization for Visual Analytics Offloading Bo Chen, Zhisheng Yan, and Klara Nahrstedt ACM MMSys (ACM International Conference on Multimedia Systems), June 2022. [PDF]
- DAO: Dynamic Adaptive Offloading for Video Analytics Taslim Murad, Anh Nguyen, and Zhisheng Yan ACM MM (ACM International Conference on Multimedia), October 2022. [PDF]
Funding
This project is sponsored by the National Science Foundation CAREER Program under award number 2144764.