Adaptive Streaming: A subjective catalog to assess the performance of objective QoE metrics
Scalable streaming has emerged as a feasible solution to resolve users' heterogeneity problems. SVC is the technology that has served as the definitive impulse for the growth of streaming adaptive systems. Systems seek to improve layer switching efficiency from the network point of view but, wi...
| Authors: | , , , , , , |
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| Format: | article |
| Publication Date: | 2014 |
| Country: | España |
| Institution: | Universidad de Oviedo (UNIOVI) |
| Repository: | RUO. Repositorio Institucional de la Universidad de Oviedo |
| Language: | English |
| OAI Identifier: | oai:digibuo.uniovi.es:10651/31190 |
| Online Access: | http://hdl.handle.net/10651/31190 https://dx.doi.org/10.5296/npa.v6i2.5461 |
| Access Level: | Open access |
| Keyword: | Scalable Video Coding (SVC) |
| Summary: | Scalable streaming has emerged as a feasible solution to resolve users' heterogeneity problems. SVC is the technology that has served as the definitive impulse for the growth of streaming adaptive systems. Systems seek to improve layer switching efficiency from the network point of view but, with increasing importance, without jeopardizing user perceived video quality, i.e., QoE. We have performed extensive subjective experiments to corroborate the preference towards adaptive systems when compared to traditional non-adaptive systems. The resulting subjective scores are correlated with most relevant Full Reference (FR) objective metrics. We obtain an exponential relationship between human decisions and the same decisions expressed as a difference of objective metrics. A strong correlation with subjective scores validates objective metrics to be used as aid in the adaptive decision taking algorithms to improve overall systems performance. Results show that, among the evaluated objective metrics, PSNR is the metric that provide worse results in terms of reproducing the human decisions |
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