IEICE TRANSACTIONS on Communications
A Quality-Level Selection for Adaptive Video Streaming with Scalable Video Coding
Summary :
In this paper, we propose a quality-level selection method for adaptive video streaming with scalable video coding (SVC). The proposed method works on the client with the dynamic adaptive streaming over HTTP (DASH) with SVC. The proposed method consists of two components: introducing segment group and a buffer-aware layer selection algorithm. In general, quality of experience (QoE) performance degrades due to stalling (playback buffer underflow), low playback quality, frequent quality-level switching, and extreme-down quality switching. The proposed algorithm focuses on reducing the frequent quality-level switching, and extreme-down quality switching without increasing stalling and degrading playback quality. In the proposed method, a SVC-DASH client selects a layer every G segments, called a segment group to prevent frequent quality-level switching. In addition, the proposed method selects the quality of a layer based on a playback buffer in a layer selection algorithm for preventing extreme-down switching. We implement the proposed method on a real SVC-DASH system and evaluate its performance by subjective evaluations of multiple users. As a result, we confirm that the proposed algorithm can obtain better mean opinion score (MOS) value than a conventional SVC-DASH, and confirm that the proposed algorithm is effective to improve QoE performance in SVC-DASH.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E102-B No.4 pp.824-831
- Publication Date
- 2019/04/01
- Publicized
- 2018/10/22
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2017EBP3432
- Type of Manuscript
- PAPER
- Category
- Network
Authors
Shungo MORI
Sophia University
Masaki BANDAI
Sophia University
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Shungo MORI, Masaki BANDAI, "A Quality-Level Selection for Adaptive Video Streaming with Scalable Video Coding" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 4, pp. 824-831, April 2019, doi: 10.1587/transcom.2017EBP3432.
Abstract: In this paper, we propose a quality-level selection method for adaptive video streaming with scalable video coding (SVC). The proposed method works on the client with the dynamic adaptive streaming over HTTP (DASH) with SVC. The proposed method consists of two components: introducing segment group and a buffer-aware layer selection algorithm. In general, quality of experience (QoE) performance degrades due to stalling (playback buffer underflow), low playback quality, frequent quality-level switching, and extreme-down quality switching. The proposed algorithm focuses on reducing the frequent quality-level switching, and extreme-down quality switching without increasing stalling and degrading playback quality. In the proposed method, a SVC-DASH client selects a layer every G segments, called a segment group to prevent frequent quality-level switching. In addition, the proposed method selects the quality of a layer based on a playback buffer in a layer selection algorithm for preventing extreme-down switching. We implement the proposed method on a real SVC-DASH system and evaluate its performance by subjective evaluations of multiple users. As a result, we confirm that the proposed algorithm can obtain better mean opinion score (MOS) value than a conventional SVC-DASH, and confirm that the proposed algorithm is effective to improve QoE performance in SVC-DASH.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2017EBP3432/_p
Copy
@ARTICLE{e102-b_4_824,
author={Shungo MORI, Masaki BANDAI, },
journal={IEICE TRANSACTIONS on Communications},
title={A Quality-Level Selection for Adaptive Video Streaming with Scalable Video Coding},
year={2019},
volume={E102-B},
number={4},
pages={824-831},
abstract={In this paper, we propose a quality-level selection method for adaptive video streaming with scalable video coding (SVC). The proposed method works on the client with the dynamic adaptive streaming over HTTP (DASH) with SVC. The proposed method consists of two components: introducing segment group and a buffer-aware layer selection algorithm. In general, quality of experience (QoE) performance degrades due to stalling (playback buffer underflow), low playback quality, frequent quality-level switching, and extreme-down quality switching. The proposed algorithm focuses on reducing the frequent quality-level switching, and extreme-down quality switching without increasing stalling and degrading playback quality. In the proposed method, a SVC-DASH client selects a layer every G segments, called a segment group to prevent frequent quality-level switching. In addition, the proposed method selects the quality of a layer based on a playback buffer in a layer selection algorithm for preventing extreme-down switching. We implement the proposed method on a real SVC-DASH system and evaluate its performance by subjective evaluations of multiple users. As a result, we confirm that the proposed algorithm can obtain better mean opinion score (MOS) value than a conventional SVC-DASH, and confirm that the proposed algorithm is effective to improve QoE performance in SVC-DASH.},
keywords={},
doi={10.1587/transcom.2017EBP3432},
ISSN={1745-1345},
month={April},}
Copy
TY - JOUR
TI - A Quality-Level Selection for Adaptive Video Streaming with Scalable Video Coding
T2 - IEICE TRANSACTIONS on Communications
SP - 824
EP - 831
AU - Shungo MORI
AU - Masaki BANDAI
PY - 2019
DO - 10.1587/transcom.2017EBP3432
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2019
AB - In this paper, we propose a quality-level selection method for adaptive video streaming with scalable video coding (SVC). The proposed method works on the client with the dynamic adaptive streaming over HTTP (DASH) with SVC. The proposed method consists of two components: introducing segment group and a buffer-aware layer selection algorithm. In general, quality of experience (QoE) performance degrades due to stalling (playback buffer underflow), low playback quality, frequent quality-level switching, and extreme-down quality switching. The proposed algorithm focuses on reducing the frequent quality-level switching, and extreme-down quality switching without increasing stalling and degrading playback quality. In the proposed method, a SVC-DASH client selects a layer every G segments, called a segment group to prevent frequent quality-level switching. In addition, the proposed method selects the quality of a layer based on a playback buffer in a layer selection algorithm for preventing extreme-down switching. We implement the proposed method on a real SVC-DASH system and evaluate its performance by subjective evaluations of multiple users. As a result, we confirm that the proposed algorithm can obtain better mean opinion score (MOS) value than a conventional SVC-DASH, and confirm that the proposed algorithm is effective to improve QoE performance in SVC-DASH.
ER -
English
