360-Degree Video Bandwidth Reduction: Technique and Approaches Comprehensive Review

Wong, En Sing and Abdul Wahab, Nur Haliza and Saeed, Faisal and Alharbi, Nouf (2022) 360-Degree Video Bandwidth Reduction: Technique and Approaches Comprehensive Review. Applied Sciences, 12 (15). ISSN 2076-3417

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Abstract

Recently, the usage of 360-degree videos has prevailed in various sectors such as education, real estate, medical, entertainment and more. The development of the Virtual World “Metaverse” demanded a Virtual Reality (VR) environment with high immersion and a smooth user experience. However, various challenges are faced to provide real-time streaming due to the nature of highresolution 360-degree videos such as high bandwidth requirement, high computing power and low delay tolerance. To overcome these challenges, streaming methods such as Dynamic Adaptive Streaming over HTTP (DASH), Tiling, Viewport-Adaptive and Machine Learning (ML) are discussed. Moreover, the superiorities of the development of 5G and 6G networks, Mobile Edge Computing (MEC) and Caching and the Information-Centric Network (ICN) approaches to optimize the 360- degree video streaming are elaborated. All of these methods strike to improve the Quality of Experience (QoE) and Quality of Service (QoS) of VR services. Next, the challenges faced in QoE modeling and the existing objective and subjective QoE assessment methods of 360-degree video are presented. Lastly, potential future research that utilizes and further improves the existing methods substantially is discussed. With the efforts of various research studies and industries and the gradual development of the network in recent years, a deep fake virtual world, “Metaverse” with high immersion and conducive for daily life working, learning and socializing are around the corner.

Item Type:	Article
Identification Number:	10.3390/app12157581
Dates:	Date Event 21 June 2022 Accepted 28 June 2022 Published Online
Uncontrolled Keywords:	Virtual Reality (VR); 360-degree video; bandwidth reduction; metaverse; DASH; tiling; viewport-adaptive; machine learning; network optimization; Quality of Experience (QoE)
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science CAH11 - computing > CAH11-01 - computing > CAH11-01-05 - artificial intelligence
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Faisal Saeed
Date Deposited:	11 Aug 2022 10:15
Last Modified:	11 Aug 2022 10:15
URI:	https://www.open-access.bcu.ac.uk/id/eprint/13466