On the Impact of Burst Loss for QoE-Based Performance Evaluations for Video Streaming

Autor(en): Laniewski, D.
Schutz, B.
Aschenbruck, N. 
Herausgeber: Tan, H.-P.
Khoukhi, L.
Oteafy, S.
Stichwörter: Burst Loss; Computer networks; H.264; H.265 HEVC; Loss patterns; Multi methods; Multimedia networking; Packet loss; Peak signal to noise ratio; Performance Evaluation; Performance metrices; PSNR; Quality control; Quality of Experience; Quality of experience (QoE); RTP; Signal to noise ratio; SSIM; Structural similarity, Quality of service; Video Streaming; Video streaming, Application scenario; VMAF
Erscheinungsdatum: 2020
Herausgeber: Institute of Electrical and Electronics Engineers Inc.
Journal: Proceedings - 2020 IEEE 45th Local Computer Networks Symposium on Emerging Topics in Networking, LCN Symposium 2020
Startseite: 78
Seitenende: 87
Zusammenfassung: 
In the broad area of performance evaluation of multimedia networking mechanisms, quality of experience (QoE) assessments are often used as a performance metric. Even though intensive efforts have been made to understand the impact of packet loss on QoE for different application scenarios, there is no consensus about how specific packet loss patterns impact the QoE for RTP video streaming. In this paper, we conduct an extensive study on the impact of uniformly distributed random and burst loss on the QoE-metrics Peak-Signal-to-Noise-Ratio (PSNR), Structural Similarity (SSIM), and Video Multi-Method Assessment Fusion (VMAF). Overall, our study indicates that for QoE-based performance evaluations, it is in most cases sufficient to only consider easier to understand and easier to model uniformly distributed random loss. © 2020 IEEE.
Beschreibung: 
Conference of 45th IEEE Local Computer Networks Symposium on Emerging Topics in Networking, LCN Symposium 2020 ; Conference Date: 17 November 2020 Through 19 November 2020; Conference Code:167664
ISBN: 9781728183145
DOI: 10.1109/LCNSymposium50271.2020.9363272
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102648094&doi=10.1109%2fLCNSymposium50271.2020.9363272&partnerID=40&md5=181e6c17ba0e2b3a63a4c15a809e13f1

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