Paper Info
Title
Video is a Cube
Abstract
Quality of experience (QoE) is becoming increasingly important in signal processing applications. In taking inspiration from chemometrics, we provide an introduction to the design of video quality metrics by using data analysis methods, which are different from traditional approaches. These methods do not necessitate a complete understanding of the human visual system (HVS). We use multidimensional data analysis, an extension of well-established data analysis techniques, allowing us to better exploit higher-dimensional data. In the case of video quality metrics, it enables us to exploit the temporal properties of video more properly; the complete three-dimensional structure of the video cube is taken into account in metrics' design. Starting with the well-known principal component analysis and an introduction to the notation of multiway arrays, we then present their multidimensional extensions, delivering better quality prediction results. Although we focus on video quality, the presented design principles can easily be adapted to other modalities and to even higher dimensional data sets as well.
Year
DOI
Venue
2011
10.1109/MSP.2011.942468
Signal Processing Magazine, IEEE
Keywords
Field
DocType
quality of service,video signal processing,data analysis techniques,data sets,human visual system,multidimensional analysis,multidimensional data analysis,quality of experience,signal processing applications,video quality metrics
Data mining,Data analysis,Human visual system model,Computer science,Multidimensional analysis,Quality of service,Theoretical computer science,Quality of experience,Artificial intelligence,Video quality,Computer vision,Feature extraction,Video tracking
Journal
Volume
Issue
ISSN
28
6
1053-5888
Citations 
PageRank 
References 
15
0.74
8
Authors
4
Name
Order
Citations
PageRank
christian keimel1242.39
Martin Rothbucher2233.58
Hao Shen322432.93
Klaus Diepold443756.47