Gene

World Wide Web

Statistics

Robustness (evolution)

Real-time computing

Quality of experience

Operating system

Quality of service

Telecommunications

Economics

Biochemistry

Data mining

Coding (social sciences)

Computer science

Metadata

Bitstream

Computer network

Software

Decoding methods

Database

Mathematics

Operations management

Video quality

Artificial intelligence

Chemistry

Metric (unit)

Reference software

This paper describes an open dataset and software for ITU-T Ree. P.1203. As the first standardized Quality of Experience model for audiovisual HTTP Adaptive Streaming (HAS), it has been extensively trained and validated on over a thousand audiovisual sequences containing HAS-typical effects (such as stalling, coding artifacts, quality switches). Our dataset comprises four of the 30 official subjective databases at a bitstream feature level. The paper also includes subjective results and the model performance. Our software for the standard was made available to the public, too, and it is used for all the analyses presented. Among other previously unpublished details, we show the significant performance improvements of using bitstream-based models over metadata-based ones for video quality analysis, and the robustness of combining classical models with machine-learning-based approaches for estimating user QoE.

HTTP adaptive streaming QoE estimation with ITU-T rec. P. 1203