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A Content-Aware Bitrate Selection Method Using Multi-Step Prediction for 360-Degree Video Streaming
文献摘要:
A content-aware multi-step prediction control (CAMPC) algorithm is proposed to determine the bitrate of 360-degree videos, aim?ing to enhance the quality of experience (QoE) of users and reduce the cost of video content providers (VCP). The CAMPC algorithm first em?ploys a neural network to generate the content richness and combines it with the current field of view (FOV) to accurately predict the probabil?ity distribution of tiles being viewed. Then, for the tiles in the predicted viewport which directly affect QoE, the CAMPC algorithm utilizes a multi-step prediction for future system states, and accordingly selects the bitrates of multiple subsequent steps, instead of an instantaneous state. Meanwhile, it controls the buffer occupancy to eliminate the impact of prediction errors. We implement CAMPC on players by building a 360-degree video streaming platform and evaluating other advanced adaptive bitrate (ABR) rules through the real network. Experimental re?sults show that CAMPC can save 83.5% of bandwidth resources compared with the scheme that completely transmits the tiles outside the viewport with the Dynamic Adaptive Streaming over HTTP (DASH) protocol. Besides, the proposed method can improve the system utility by 62.7% and 27.6% compared with the DASH official and viewport-based rules, respectively.
文献关键词:
作者姓名:
GAO Nianzhen;YU Yifang;HUA Xinhai;FENG Fangzheng;JIANG Tao
作者机构:
Huazhong University of Science and Technology,Wuhan 430074,China;ZTE Corporation,Shenzhen 518057,China
引用格式:
[1]GAO Nianzhen;YU Yifang;HUA Xinhai;FENG Fangzheng;JIANG Tao-.A Content-Aware Bitrate Selection Method Using Multi-Step Prediction for 360-Degree Video Streaming)[J].中兴通讯技术(英文版),2022(04):96-109
A类:
Bitrate,CAMPC,bitrate,ploys,viewport,bitrates
B类:
Content,Aware,Selection,Method,Using,Multi,Step,Prediction,Degree,Video,Streaming,content,aware,prediction,algorithm,proposed,determine,degree,videos,aim,enhance,quality,experience,QoE,users,reduce,cost,providers,VCP,first,neural,network,generate,richness,combines,current,field,FOV,accurately,probabil,distribution,tiles,being,viewed,Then,predicted,which,directly,affect,utilizes,future,system,states,accordingly,selects,multiple,subsequent,steps,instead,instantaneous,Meanwhile,controls,buffer,occupancy,eliminate,impact,errors,We,implement,players,by,building,streaming,platform,evaluating,other,advanced,adaptive,ABR,rules,through,real,Experimental,sults,show,that,can,save,bandwidth,resources,compared,scheme,completely,transmits,outside,Dynamic,Adaptive,over,HTTP,DASH,protocol,Besides,method,improve,utility,official,respectively
AB值:
0.565971
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Zhenni Li;Yujie Li;Benying Tan;Shuxue Ding;Shengli Xie-School of Automation,Guangdong University of Technology,Guangzhou 510006,and also with the Guangdong-Hong Kong-Macao Joint Laboratory for Smart Discrete Manufacturing,Guangdong University of Technology(GDUT),Guangzhou 510006,China;School of Artificial Intelligence,Guilin University of Electronic Technology,Guilin 541004,China,and also with the National Institute of Advanced Industrial Science and Technology,Tsukuba,Ibaraki 305-8560,Japan;School of Artificial Intelligence,Guilin University of Electronic Technology,Guilin 541004,China;Key Laboratory of Intelligent Information Processing and System Integration of IoT(GDUT),Ministry of Education,and with Guangdong Key Laboratory of IoT Information Technology(GDUT),Guangzhou 510006,China
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