Abstract

Video quality demanded by the end user must result in the best possible Quality of Experience (QoE). QoE assesment as well as its integration into video streaming algorithms is a complex problem that demands a comprehensive design of subjective databases and video quality metrics. This paper presents an analysis of different video quality metrics and their usability for QoE measurement for HTTP based adaptive streaming (HAS). To compare the metrics, the LIVE-NFLX-II database is used.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.