Design/methodology/approach- We assess 8 NR metrics, alongside a lightweight FR metric, using VQM as benchmark in a self developed network-impaired video dataset. Our study covers a range of methods, a diverse set of video types and encoding conditions, and a variety of network impairment test-cases.
Findings- We show the extent by which packet loss affects different video types, correlating the accuracy of NR metrics to the FR benchmark. Our study helps identifying the conditions under which simple metrics may be used effectively and indicates an avenue to control the quality of streaming systems.
Originality/value- Most studies in literature have focused on assessing streams that are either unaffected by the network (e.g., looking at the effects of video compression algorithms) or are affected by synthetic network impairments (i.e. via simulated network conditions). We show that when streams are affected by real network conditions, assessing QoE becomes even harder, as the existing metrics perform poorly.
|Journal||International Journal of Pervasive Computing and Communications|
|Publication status||Published - 1 Apr 2016|
- Quality of Experience
- No-Reference Video Quality
- Netwoek Impaired Videos
Mocanu, Decebal C. (Recipient), 2017
Prize: Other › Career, activity or publication related prizes (lifetime, best paper, poster etc.) › Scientific