Quality Assessment of Audiovisual Communication in Videotelephony: New ITU-T P.940 and P Suppl.31
Year: 2025
Type: article
Abstract: With the rapid development of communication technologies, videotelephony services enabled by consumer technology have gradually become an indispensable means of communication in people’s daily life, work, and study. It is of crucial importance to perform scientific and accurate assessments for the quality of experience perceived by consumers. Moreover, with the continuous advancement of media codec and transmission technologies, consumers’ expectation for service quality have increased, necessitating an expansion and improvement of the videotelephony quality assessment models or tools. This paper presents subjective datasets collaboratively developed by four labs and investigates objective assessment methods. The subjective datasets are constructed from two types of tests: the non-interactive audiovisual material subjective tests and the interactive conversational subjective tests. For non-interactive subjective test dataset, the following factors’ impact on video quality are analyzed: codec type, device type, spatial complexity and temporal complexity. For interactive subjective test dataset, the correlations between interaction experience and influencing factors (audio delay, video delay and network transmission degradation) are analyzed. Furthermore, the subjective test datasets were instrumental in the development of the objective assessment model in the recently published ITU-T Recommendation P.940. This paper provides a comparative analysis between the models recommended in P.940 and G.1070 in terms of video quality, interaction experience and overall videotelephony quality.
Authors: Mengying Liu, Lei Yang, Vincent Barriac, Yaosi Hu, Jose Joskowicz, Rafael Sotelo, Shijun Zhang, Zhenzhong Chen, Alejandra Armendariz, Martin Wildbaum, Guillermo Fiorina
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415125076