| 研究課題/領域番号 |
20H04174
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| 研究機関 | 電気通信大学 |
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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)
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| 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(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(准教授) (40759891)
Kien Nguyen 千葉大学, 大学院工学研究院, 准教授 (80647222)
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| 研究期間 (年度) |
2020-04-01 – 2024-03-31
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| キーワード | point cloud / video streaming / MEC / AI / VR/AR/MR |
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| 研究実績の概要 |
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.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
非常に良い結果を得ることができ、重要な問題を解決することができました。
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| 今後の研究の推進方策 |
Next year I will focus on the following two technical challenges:
1. AI-empowered point cloud video transmission: We will use AI technologies (such as transformer, LSTM,) to predict the user viewing angle and efficiently and adaptively utilize nearby available communication and computing resources (including the resource provided MEC) to provide required computation for encoding, transcoding and decoding, where existing resource allocation schemes cannot be directly applied.
2. Prototype building and scheme adjustment: The proposed point cloud video streaming system will be implemented based on off-the-shelf devices and the proposed schemes will be adjusted according to their performance. We will also summarize the results and conclude this project.
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