Realistic video sequences for subjective QoE analysis

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Date
2022
Authors
Hodzic, Kerim
Cosovic, Mirsad
Mrdovic, Sasa
Quinlan, Jason J.
Raca, Darijo
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Association for Computing Machinery (ACM)
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Abstract
Multimedia streaming over the Internet (live and on demand) is the cornerstone of modern Internet carrying more than 60% of all traffic. With such high demand, delivering outstanding user experience is a crucial and challenging task. To evaluate user QoE many researchers deploy subjective quality assessments where participants watch and rate videos artificially infused with various temporal and spatial impairments. To aid current efforts in bridging the gap between the mapping of objective video QoE metrics to user experience, we developed DashReStreamer, an open-source framework for re-creating adaptively streamed video in real networks. DashReStreamer utilises a log created by a HAS algorithm run in an uncontrolled environment (i.e., wired or wireless networks), encoding visual changes and stall events in one video file. These videos are applicable for subjective QoE evaluation mimicking realistic network conditions. To supplement DashReStreamer, we re-create 234 realistic video clips, based on video logs collected from real mobile and wireless networks. In addition our dataset contains both video logs with all decisions made by the HASalgorithm and network bandwidth profile illustrating throughput distribution. We believe this dataset and framework will permit other researchers in their pursuit for the final frontier in understanding the impact of video QoE dynamics.
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QoE , Dataset , Mobility , Throughput , Context information , Adaptive video streaming , 3G , 4G , 5G , WiFi
Citation
Hodzic, K., Cosovic, M., Mrdovic, S., Quinlan, J. J. and Raca, D. (2022) ‘Realistic video sequences for subjective QoE analysis’, MMSys '22: Proceedings of the 13th ACM Multimedia Systems Conference, Athlone, Ireland, 14-17 June, pp. 246-251. doi: 10.1145/3524273.3532894
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© 2022, Association for Computing Machinery. This is the author's version of the work. The definitive Version of Record is available at: https://dx.doi.org/10.1145/3524273.3532894.