Christian Keimel
Christian Keimel
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Evaluation of video quality fluctuations using pattern categorisation
Fluctuations of video quality over time can have a significant influence on the overall perceived quality as represented by the QoE. …
Clemens Horch
,
Julian Habigt
,
Christian Keimel
,
Klaus Diepold
PDF
BibTeX
DOI
Length-independent refinement of video quality metrics based on multiway data analysis
In previous publications it has been shown that no-reference video quality metrics based on a data analysis approach rather than on …
Clemens Horch
,
Christian Keimel
,
Julian Habigt
,
Klaus Diepold
PDF
BibTeX
DOI
The TUM High Definition Video Data Sets
The research on video quality metrics depends on the results from subjective testing for both the design and development of metrics, …
Christian Keimel
,
Arne Redl
,
Klaus Diepold
PDF
BibTeX
DOI
QualityCrowd -- A framework for crowd-based quality evaluation
Video quality assessment with subjective testing is both time consuming and expensive. An interesting new approach to traditional …
Christain Keimel
,
Julian Habigt
,
Clemens Horch
,
Klaus Diepold
PDF
BibTeX
DOI
Video quality evaluation in the cloud
Video quality evaluation with subjective testing is both time consuming and expensive. An interesting new approach to traditional …
Christian Keimel
,
Julian Habigt
,
Clemens Horch
,
Klaus Diepold
PDF
BibTeX
DOI
Improving the prediction accuracy of video quality metrics
To improve the prediction accuracy of visual quality metrics for video we propose two simple steps: temporal pooling in order to gain a …
Christian Keimel
,
Tobias Oelbaum
,
Klaus Diepold
PDF
BibTeX
DOI
Rule-Based No-Reference Video Quality Evaluation Using Additionally Coded Videos
This contribution presents a no-reference video quality metric, which is based on a set of simple rules that assigns a given video to …
Tobias Oelbaum
,
Christian Keimel
,
Klaus Diepold
PDF
BibTeX
DOI
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