AI-empowered Point Cloud Video Streaming

AI赋能的点云视频流

• 批准号: 20H04174
• 负责人: 劉 志
• 金额: $ 10.98万
• 依托单位: The University of Electro-Communications
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 2020
• 资助国家: 日本
• 起止时间: 2020-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-20H04174/
• 关键词: point cloud video; video streaming; AI; MEC; VR/AR/MR; point cloud

Point cloud video is the most popular representation of hologram and volumetric video, which is the medium to precedent natural content in VR/AR/MR, and is expected to be the next generation video by providing users with better immersive viewing experience. Point cloud video has wide applications in Society 5.0 such as for online education and entertainment. To further enhance these applications, networked point cloud video is in critical demand. This project aims to solve the core technical questions towards a high quality point cloud video streaming and promote the applications of point cloud video in Society 5.0.In the past year, we have developed AI-based streaming algorithms that deliver enhanced video quality to users. Additionally, we have optimized the MEC to provide short-delay additional computation capability. To evaluate performance, we have created prototypes. Some of our findings have been published or submitted to IEEE/ACM journals and conferences.

点云视频是全息图和体积视频的最流行表示，是VR/AR/MR中自然内容的先驱，并有望通过为用户提供更好的沉浸式观看体验而成为下一代视频。点云视频在社会5.0中具有广泛的应用，例如在线教育和娱乐。为了进一步增强这些应用程序，网络点云视频是至关重要的需求。该项目旨在解决高质量点云视频流的核心技术问题，推动点云视频在社会5.0中的应用。在过去的一年里，我们开发了基于AI的流媒体算法，为用户提供更高的视频质量。此外，我们还优化了MEC，以提供短延迟的额外计算能力。为了评估性能，我们创建了原型。我们的一些研究结果已发表或提交给IEEE/ACM期刊和会议。

项目成果

Collaborative Learning of Communication Routes in Edge-Enabled Multi-Access Vehicular Environment

• DOI: 10.1109/tccn.2020.3002253
• 发表时间: 2020-12-01
• 期刊: IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
• 影响因子: 8.6
• 作者: Wu, Celimuge;Liu, Zhi;Li, Jie
• 通讯作者: Li, Jie

Congestion-Aware Scheduling for Software-Defined SAG Networks

软件定义 SAG 网络的拥塞感知调度

• DOI: 10.1109/tnse.2021.3055372
• 发表时间: 2021
• 期刊: IEEE Transactions on Network Science and Engineering
• 影响因子: 6.6
• 作者: Tao Xiaoyi;Ota Kaoru;Dong Mianxiong;Qi Heng;Li Keqiu
• 通讯作者: Li Keqiu

Joint Communication and Computational Resource Allocation for QoE-driven Point Cloud Video Streaming

• DOI: 10.1109/icc40277.2020.9148922
• 发表时间: 2020-01
• 期刊: ICC 2020 - 2020 IEEE International Conference on Communications (ICC)
• 作者: Jie Li;Cong Zhang;Zhi Liu;Wei Sun;Qiyue Li

Healthchain: Secure EMRs Management and Trading in Distributed Healthcare Service System

Healthchain：分布式医疗服务系统中安全的电子病历管理和交易

• DOI: 10.1109/jiot.2020.3038721
• 发表时间: 2021-05
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Li Chaoyang;Dong Mianxiong;Li Jian;Xu Gang;Chen Xiubo;Ota Kaoru
• 通讯作者: Ota Kaoru

Optimal transmission of multi-quality tiled 360 VR video in MIMO-OFDMA systems

MIMO-OFDMA 系统中多质量平铺 360 VR 视频的优化传输

• 发表时间: 2021
• 作者: Chengjun Guo;Ying Cui;Zhi Liu;Derrick Wing Kwan Ng
• 通讯作者: Derrick Wing Kwan Ng