Post on 06-Jul-2018
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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Università degli Studi di Modena e Reggio EmiliaFacoltà di Ingegneria “Enzo Ferrari”
Corso di Laurea Specialistica inIngegneria delle Telecomunicazioni
An ExperimentalAnalysis of
objective video
quality assessmentmethods
Relatore:
Prof. Ing. Maria LuisaMerani
Tesi di:
Luciana agnetta
Anno Accademico!"##$!"#!
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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!at is "oE#%uality of Experience describes the &quality from
the perspective of the user or consumer 'i.e.vie(er)* (ith a focus on the perceived quality ofthe content 'or more comprehensively* userexperience).+ ',in-ler)
$o% to measure &ideo "oE#hrough /ideo %uality Assessment '/%A)methods* i.e. methods that calculate the value ofa quality metric '/%M)* an index that representsthe level of quality of a video .
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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Su'(ective vs o'(ective &") *+,-.
0ubjective /%A methods
Pros1 accurate and reliable
ons1 expensive and timeconsuming
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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2bjective /%A methods
Su'(ective vs o'(ective &") *-,-.
Pros1 cheap and fast.
ons1 their performance cannot be evaluated (ithout asubjective benchmar-3 usable only for codec evaluation3either inaccurate or computationally expensive.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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#. Experimental based comparative analysisof exististing objective /%A methods
!. haracteri4ation of the ontent type of
videos through the calculation ofomplexity and Motion factors
5. Introduction of a ne( Prediction Modelfor /%A
Main Contri'utions
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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Met!od
#" ra( yuv videos representing natural scenesencoded at #" di6erent bit rates 'for a total of#"" test videos) (ith 7.!89$A/ scheme
0oft(are implementation of #" objective
/%A methods
Available subjective scores for each of the#"" videos 'research of :$e university(here I (or-ed on my master project)
Performance evaluation of each methodusing as benchmar- the subjective scores
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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+/ 0ormalized &"M results *+,-.he quality of each impaired video (as calculated (ith each/%Ms using the correspondent ra( video as reference.
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+/ 0ormalized &"M results *-,-.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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-/ C!aracterization o1 t!e Content T2pe *+,-.
, 0 ≤ C
≤1
, 0 ≤ M
≤1
(here ;itsI are the bits of coded Intra 'I<)
frames* ;itsP are the bits of coded Inter 'P<)
frames* %PI is the average quanti4ation
parameter of I<frames and %PP
is the
average quanti4ation parameter of P<frames. and M factors depend on readily availableparameters* thus they can conveniently beemployed by a non<intrusive video contentblind quality model
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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-/ C!aracterization o1 t!e Content T2pe *-,-.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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&ideos %it! Lo%est )verage measured 3ualit2
&ideos %it! $ig!est )verage measured 3ualit2
he ! videos (hich havethe lo(est averagemeasured quality accordingto all metrics are also theones (ith the highest levelof motion and complexity.
he videos (ith the
highest averagemeasured quality arealso the ones (ith thelo(est level of motionand complexity.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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4enc!mar5ing o1 6'(ective &") met!ods
=ormali4ation of the output of each /%M
>itting of normali4ed values vs ;it ?ate foreach /%MPerformance of 2bjective /%A (ith respectto subjective results is evaluated by t(omain attributes 1
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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7/ T!e ne% 8rediction Model *+,7.
he model used to ma-e the prediction ofvideo quality is the follo(ing asymptoticexponential function1
(here a is set to # for ensuring theconvergence of the maximum quality
index to #3 and M are the formerlypresented complexity and motionparameters3 ;r is the bit rate3 b* c and dare the parameters optimi4ed for a
generic video type.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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7/ T!e ne% 8rediction Model *-,7.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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7/ T!e ne% 8rediction Model *7,7.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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My metric provides a good trade<o61
computationally comparable to existing@simple 'yet inaccurate) metrics3
comparably as accurate as M2/IE '(hich isunviable due to high computational
requirements).
ConclusionsExisting /%Ms are either inaccurate or
computationally and memory intensive.
Existing /%Ms are either inaccurate orcomputationally and memory intensive
My metric can be used not only for codecevaluation but also for real timeapplications because it depends on
readily available parameters.
8/17/2019 An Experimental Analysis of Objective Video Quality Assessment Methods
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Extend tests to net(or-<impaired videos
Future or5
onsider broader test matrix
>urther study the t(o cases in (hichne( metric does not correlate (ell(ith M2/IE