Name
Abstract | ||
|---|---|---|
In real-life applications, no-reference metrics are more useful than full-reference metrics. To design such metrics, we apply data analysis methods to objectively measurable features and to data originating from subjective testing. Unfortunately, the information about temporal variation of quality is often lost due to the temporal pooling over all frames. Instead of using temporal pooling, we have recently designed a H.264/AVC bitstream no-reference video quality metric employing multiway Partial Least Squares Regression (PLSR), which leads to an improved prediction performance. In this contribution we will utilize multiway PLSR to design a hybrid metric that combines both bitstream-based features with pixel-based features. Our results show that the additional inclusion of the pixel-based features improves the quality prediction even further. |
Year | Venue | Keywords |
|---|---|---|
2012 | European Signal Processing Conference | Video quality metric,no-reference metric,hybrid metric,multilinear data analysis,multiway PLSR,trilinear PLS |
Field | DocType | ISSN |
Pattern recognition,Data analysis,Regression analysis,Partial least squares regression,Pooling,Pixel,Artificial intelligence,Bitstream,Video quality,Mathematics | Conference | 2076-1465 |
Citations | PageRank | References |
5 | 0.41 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Keimel | 1 | 150 | 12.00 |
| Julian Habigt | 2 | 79 | 6.90 |
| Klaus Diepold | 3 | 437 | 56.47 |