Status | 已发表Published |
Title | Toward Low-Latency and High-Quality Adaptive 360° Streaming |
Creator | |
Date Issued | 2023-05-01 |
Source Publication | IEEE Transactions on Industrial Informatics
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ISSN | 1551-3203 |
Volume | 19Issue:5Pages:6326-6336 |
Abstract | Advanced 360° video streaming is essential for high-quality communication and industrial video applications, supporting novel and interactive visual experiences that promote consumption. However, due to the inherent fluctuations in communication networks, hardware resources, and power costs, a tradeoff needs to be achieved between occupying network bandwidth and guaranteeing 360° visual quality. To address this issue, this article proposes a quality-aware global optimization solution that combines different types of sensory characteristics to further enhance the 360° streaming efficiency in cellular networks. First, considering the characteristics of 360° video, each frame is divided into three different regions based on a proposed field-of-view prediction method. Second, a new region-based rate-distortion model reflecting the bitrate-quality relationship is proposed. The divided regions are represented by different rate-distortion models. In addition, a rate-distortion model parameter update strategy with robustness to region changes is proposed to further guarantee transmission performance. Finally, we propose a globally optimized adaptive bitrate allocation algorithm to optimize 360° mobile streaming, which uses both the rate-distortion models and viewpoint prediction results. Evaluation results indicate that the proposed method outperforms state-of-the-art approaches in terms of several quality of experience objectives under various network conditions. |
Keyword | 360° video field of view (FoV) industrial application quality of experience (QoE) rate-distortion video streaming |
DOI | 10.1109/TII.2022.3192398 |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Automation & Control Systems ; Computer Science ; Engineering |
WOS Subject | Automation & Control Systems ; Computer Science, Interdisciplinary Applications ; Engineering, Industrial |
WOS ID | WOS:000982913400007 |
Scopus ID | 2-s2.0-85135231567 |
Citation statistics | |
Document Type | Journal article |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/10604 |
Collection | Faculty of Science and Technology |
Corresponding Author | Zhou, Mingliang |
Affiliation | 1.Chongqing University,School of Computer Science,Chongqing,400044,China 2.BNU-UIC Institute of Artificial Intelligence and Future Networks Beijing Normal University,Bnu Zhuhai,Guangdong Key Lab of Ai and Multi-Modal Data Processing,BNU-HKBU United International College,Guangdong,Zhuhai,519087,China |
Recommended Citation GB/T 7714 | Wei, Xuekai,Zhou, Mingliang,Jia, Weijia. Toward Low-Latency and High-Quality Adaptive 360° Streaming[J]. IEEE Transactions on Industrial Informatics, 2023, 19(5): 6326-6336. |
APA | Wei, Xuekai, Zhou, Mingliang, & Jia, Weijia. (2023). Toward Low-Latency and High-Quality Adaptive 360° Streaming. IEEE Transactions on Industrial Informatics, 19(5), 6326-6336. |
MLA | Wei, Xuekai,et al."Toward Low-Latency and High-Quality Adaptive 360° Streaming". IEEE Transactions on Industrial Informatics 19.5(2023): 6326-6336. |
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