The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 SVC(Scalable Video Coding)를 이용한 적응형 비디오 스트리밍을 위한 품질 수준 선택 방법을 제안합니다. 제안된 방법은 SVC를 사용하여 HTTP(DASH)를 통한 동적 적응형 스트리밍을 사용하여 클라이언트에서 작동합니다. 제안된 방법은 세그먼트 그룹 도입과 버퍼 인식 레이어 선택 알고리즘의 두 가지 구성 요소로 구성됩니다. 일반적으로 QoE(경험 품질) 성능은 지연(재생 버퍼 언더플로우), 낮은 재생 품질, 잦은 품질 수준 전환, 극도로 낮은 품질 전환으로 인해 저하됩니다. 제안하는 알고리즘은 지연을 증가시키지 않고 재생 품질을 저하시키지 않으면서 빈번한 품질 수준 전환과 극도로 낮은 품질 전환을 줄이는 데 중점을 둡니다. 제안하는 방법에서 SVC-DASH 클라이언트는 매 단계마다 레이어를 선택한다. G 잦은 품질 수준 전환을 방지하기 위해 세그먼트 그룹이라고 합니다. 또한, 제안하는 방법은 극한 다운 스위칭을 방지하기 위한 레이어 선택 알고리즘에서 재생 버퍼를 기반으로 레이어의 품질을 선택한다. 제안한 방법을 실제 SVC-DASH 시스템에 구현하고, 다수의 사용자의 주관적인 평가를 통해 성능을 평가한다. 결과적으로 제안하는 알고리즘이 기존 SVC-DASH보다 더 나은 MOS(Mean Opinion Score) 값을 얻을 수 있음을 확인하고, 제안하는 알고리즘이 SVC-DASH에서 QoE 성능을 향상시키는 데 효과적임을 확인합니다.
Shungo MORI
Sophia University
Masaki BANDAI
Sophia University
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부
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
부
@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},}
부
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 -