Paper Info
Title
Design of no-reference video quality metrics with multiway partial least squares regression.
Abstract
No-reference video quality metrics are becoming ever more popular, as they are more useful in real-life applications compared to full-reference metrics. One way to design such metrics is by applying data analysis methods on both objectively measurable features and data from subjective testing. Partial least squares regression (PLSR) is one such method. In order to apply such methods, however, we have to temporally pool over all frames of a video, loosing valuable information about the quality variation over time. Hence, we extend the PLSR into a higher dimensional space with multiway PLSR in this contribution and thus consider video in all its dimensions. We designed a H.264/AVC bitstream no-reference video quality metric in order to verify multiway PLSR against PLSR with respect to the prediction performance. Our results show that the inclusion of the temporal dimension with multiway PLSR improves the quality prediction and its correlation with the actual quality.
Year
DOI
Venue
2011
10.1109/QoMEX.2011.6065711
QoMEX
Keywords
Field
DocType
least squares approximations,regression analysis,video coding,H.264/AVC bitstream no-reference video quality metric,PLSR,data analysis methods,multiway partial least squares regression,no-reference video quality metrics,H.264/AVC,multilinear data analysis,multiway PLSR,no-reference metric,trilinear PLS,video quality metric
Pattern recognition,Data analysis,Regression analysis,Visualization,Computer science,Partial least squares regression,Feature extraction,Artificial intelligence,Bitstream,Video quality,Encoding (memory)
Conference
ISSN
Citations 
PageRank 
2372-7179
6
0.54
References 
Authors
7
4
Name
Order
Citations
PageRank
Christian Keimel115012.00
Julian Habigt2796.90
Manuel Klimpke360.54
Klaus Diepold443756.47