Abstract
In this paper we present a parametric model for audiovisual quality
estimation in IPTV and similar services. The proposed model takes advantage
of signal characteristics calculated at the sender (in particular related to
levels of motion in the content), but is purely parametric on the estimation
(i.e. it does not require peeking into the bitstream), which makes it
suitable for large-scale real-time monitoring applications. In order to
obtain the model, we followed the Pseudo-Subjective Quality Assessment (PSQA)
methodology, and compared different kinds of statistical estimators, namely
Multilayer Perceptrons (MLP) and Random Neural Networks (RNN).
| Original language | English |
|---|---|
| Title of host publication | Proceedings |
| Subtitle of host publication | Fifth International Workshop on Quality of Multimedia Experience, QoMEX 2013 |
| Publisher | IEEE Institute of Electrical and Electronic Engineers |
| Pages | 6-11 |
| ISBN (Electronic) | 978-1-4799-0738-0 |
| DOIs | |
| Publication status | Published - 2013 |
| MoE publication type | Not Eligible |
| Event | 5th International Workshop on Quality of Multimedia Experience, QoMEX 2013 - Klagenfurt am Wörthersee, Austria Duration: 5 Jul 2013 → 7 Jul 2013 Conference number: 5 |
Conference
| Conference | 5th International Workshop on Quality of Multimedia Experience, QoMEX 2013 |
|---|---|
| Abbreviated title | QoMEX 2013 |
| Country/Territory | Austria |
| City | Klagenfurt am Wörthersee |
| Period | 5/07/13 → 7/07/13 |
Keywords
- audiovisual quality assessment
- feature clustering
- neural network
- video quality assessment