The Waterloo Streaming Quality-of-Experience Database-IV
The diversity of video delivery pipeline poses a grand challenge to the evaluation of adaptive bitrate (ABR) streaming algorithms and objective quality-of-experience (QoE) models.
Here we introduce so-far the largest subject-rated database of its kind, namely WaterlooSQoE-IV, consisting of 1350 adaptive streaming videos created from diverse source contents, video encoders, network traces, ABR algorithms, and viewing devices.
We collect human opinions for each video with a series of carefully designed subjective experiments.
Subsequent data analysis and testing/comparison of ABR algorithms and QoE models using the database lead to a series of novel observations and interesting findings, in terms of the effectiveness of subjective experiment methodologies, the interactions between user experience and source content, viewing device and encoder type, the heterogeneities in the bias and preference of user experiences, the behaviors of ABR algorithms, and the performance of objective QoE models.
The Waterloo Quality-of-Experience IV database consists of 1,350 streaming videos (generated from 5 source videos x 2 encoders x 9 network traces x 5 ABR algorithms x 3 viewing devices). The 5 ABR algorithms include RB, BB, FastMPC, Pensieve, and RDOS.
The waterloo_sqoe4_feature.zip contains all meta data such as chunk level bitrate, rebuffering duration, spatial resolution, and MOS.
The waterloo_sqoe4_server_video.zip contains the dash videos on the server.
The waterloo_sqoe4_full.zip contains all the streaming videos in mp4.