| 研究課題/領域番号 |
20H04174
|
|---|
| 研究機関 | 電気通信大学 |
|---|
研究代表者 |
劉 志 電気通信大学, 大学院情報理工学研究科, 准教授 (90750240)
|
|---|
| 研究分担者 |
太田 香 室蘭工業大学, 大学院工学研究科, 文部科学省卓越研究員(准教授) (50713971)
李 鶴 室蘭工業大学, 大学院工学研究科, 文部科学省卓越研究員(助教) (40759891)
Kien Nguyen 千葉大学, 大学院工学研究院, 助教 (80647222)
|
|---|
| 研究期間 (年度) |
2020-04-01 – 2024-03-31
|
| キーワード | point cloud / video streaming / MEC / AI / VR/AR/MR |
|---|
| 研究実績の概要 |
Point cloud video is the most popular representation of hologram, 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 for a high quality point cloud video streaming and promote the applications of point cloud video in Society 5.0.
Towards this goal, we have mainly considered 1) how to design transmission friendly point cloud video codec, 2) how to utilize AI to build MEC for the point cloud video streaming, and 3) how to utilize AI to schedule the point cloud video streaming, in order to provide users with high quality point cloud video services.
Part of the results have been published in IEEE journals and conferences.
|
| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
According to the schedule, we focus on the survey, the codec design, MEC and transmission scheduling in the first two years. From our achievement, we can find the progress is smooth.
|
| 今後の研究の推進方策 |
Next year I will focus on the following three technical challenges:
1. AI-empowered point cloud video transmission
2. AI-inspired MEC design for point cloud video transmiission
3. prototype building and scheme adjustment
|
