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

• KANAI Kenji

  Waseda University

• WEI Bo

  Waseda University

• CHENG Zhengxue

  Waseda University

• TAKEUCHI Masaru

  Waseda University

• KATTO Jiro

  Waseda University

抄録

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.

収録刊行物

• IEICE Transactions on Communications

  IEICE Transactions on Communications E102.B (7), 1240-1247, 2019-07-01

  一般社団法人 電子情報通信学会

キーワード

• video streaming
• picture quality assessment
• MPEG-DASH
• machine learning

詳細情報

• CRID: 1390282763127227136
• NII論文ID: 130007671372
• DOI: 10.1587/transcom.2018ani0003
• ISSN: 17451345
• ISSN: 09168516
• Web Site: https://www.jstage.jst.go.jp/article/transcom/E102.B/7/E102.B_2018ANI0003/_pdf
• 本文言語コード: en
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