4.7 Article

Collaborative Virtual 3D Object Modeling for Mobile Augmented Reality Streaming Services Over 5G Networks

期刊

IEEE TRANSACTIONS ON MOBILE COMPUTING
卷 22, 期 7, 页码 3855-3869

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TMC.2022.3149543

关键词

Mobile augmented reality; virtual object modeling; mobile edge cloud; 5G networks; D2D communications

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This paper presents a collaborative virtual 3D object modeling system that leverages mobile edge cloud (MEC) and device-to-device (D2D) communication for low-latency and high-quality augmented reality (AR) streaming services over 5G networks. The system utilizes MEC for computationally intensive tasks and D2D communication for reducing transmission delay. It introduces a part-segment quality selection algorithm to control the quality of each segment based on the user's network condition. The experimental results demonstrate the superior performance of the proposed system in terms of service latency and visual 3D object quality compared to conventional systems.
This paper presents a collaborative virtual 3D object modeling system for mobile augmented reality (AR) streaming services over 5G networks. The objective of the proposed system is to provide AR streaming services with low latency and high virtual object quality by effectively leveraging mobile edge cloud (MEC) and device-to-device (D2D) communication. MEC is utilized to perform computation-intensive 3D object modeling, such as virtual object slicing and mesh simplification, with abundant computing and storage resources. D2D communication is also utilized to reduce transmission delay by sharing virtual objects of interest among adjacent users. To achieve this goal, we propose a part-segment quality selection algorithm that can control the quality of each part segment and the transmission source by considering the user's network condition. In the proposed system, all elements in the AR cloud, MEC, and mobile device are technically integrated to work together seamlessly. Finally, the proposed system is fully implemented using well-known open-source frameworks, including WebGL and AR.js. The system was then examined in real wireless network environments. The experimental results demonstrate the performance of the proposed system. The proposed system outperforms conventional systems in terms of service latency and visual 3D object quality.

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