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Open Access
Methods for Adaptive Video Streaming and Picture Quality Assessment to Improve QoS/QoE Performances

Kenji KANAI, Bo WEI, Zhengxue CHENG, Masaru TAKEUCHI, Jiro KATTO

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Summary :

This paper introduces recent trends in video streaming and four methods proposed by the authors for video streaming. Video traffic dominates the Internet as seen in current trends, and new visual contents such as UHD and 360-degree movies are being delivered. MPEG-DASH has become popular for adaptive video streaming, and machine learning techniques are being introduced in several parts of video streaming. Along with these research trends, the authors also tried four methods: route navigation, throughput prediction, image quality assessment, and perceptual video streaming. These methods contribute to improving QoS/QoE performance and reducing power consumption and storage size.

Publication
IEICE TRANSACTIONS on Communications Vol.E102-B No.7 pp.1240-1247
Publication Date
2019/07/01
Publicized
2019/01/22
Online ISSN
1745-1345
DOI
10.1587/transcom.2018ANI0003
Type of Manuscript
Special Section INVITED PAPER (Special Section on Communication Technologies and Service Qualities in Various Access Networks)
Category

Authors

Kenji KANAI
  Waseda University
Bo WEI
  Waseda University
Zhengxue CHENG
  Waseda University
Masaru TAKEUCHI
  Waseda University
Jiro KATTO
  Waseda University

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