  Measuring Quality of Experience (QoE) and integrating these measurements into
video streaming algorithms is a multi-faceted problem that fundamentally
requires the design of comprehensive subjective QoE databases and metrics. To
achieve this goal, we have recently designed the LIVE-NFLX-II database, a
highly-realistic database which contains subjective QoE responses to various
design dimensions, such as bitrate adaptation algorithms, network conditions
and video content. Our database builds on recent advancements in
content-adaptive encoding and incorporates actual network traces to capture
realistic network variations on the client device. Using our database, we study
the effects of multiple streaming dimensions on user experience and evaluate
video quality and quality of experience models. We believe that the tools
introduced here will help inspire further progress on the development of
perceptually-optimized client adaptation and video streaming strategies. The
database is publicly available at
http://live.ece.utexas.edu/research/LIVE_NFLX_II/live_nflx_plus.html.
