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jfmcarreira
2018-08-01 16:26:10 +01:00
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043_EndToEndRobustSystem/EndToEndRobustSystem.tex
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@@ -29,12 +29,12 @@ The evaluation of these methods revealed that they can efficiently increase the
Therefore, it is noticeable that each method might be optimised for different applications, video characteristics and network conditions.
To advance one step forward, a jointly robust coding method using different techniques can be used to increase the decoder video quality across difference conditions.
Such approach can be based on both the input contents and the network information, such as bitrate and packet loss conditions to optimise the robust coders to each application scenario. In order to overcome the above problem a jointly evaluation study is necessary to identify the most efficient techniques and to evaluate their performance for different conditions.
Such approach can be based on both the input contents and the network information, such as bitrate and packet loss conditions to optimise the robust coders to each application scenario. In order to overcome the above problem, a joint evaluation study is necessary to identify the most efficient techniques across different conditions.
\subsection{Comparison of the proposed methods}
In order to develop a jointly robust coder to cope with transmission errors an evaluation study was carried out, to compare the error robustness performance of the proposed methods for different conditions with each others.
In order to develop a joint robust coder to cope with transmission errors an evaluation study was carried out, to compare the error robustness performance of the proposed methods for different conditions with each others.
%This study extends the previous evaluations presented in Chapter~\ref{Chapter:ErrorResilienceTechniques}~and~\ref{Chapter:ConcealmentAwareTechniques}, as they target a wider range of test material and network conditions.
The experimental evaluation carried out in this section follows the same condition described in Section~\ref{Section3:ErrorResilienceEvaluation}.
%In order to perform a wider evaluation different bitrate and \acs{plr} were used. Table~\ref{Table6:TestVariables} illustrates the selected configurations. As shown in the table a total of 15 test sequences were used encoder using 5 different target bitrates. One should note that the main bitrate varies based on the test sequence and it is shown in third column of Table~\ref{TableTestSequences}. Different network conditions were evaluated using a total of 13 different \acs{plr}, with higher special focus on lower loss ratios, which are more relevant to modern video streaming applications.
@@ -67,7 +67,7 @@ Figures~\ref{Figure6:AverageQualityMain}~and~\ref{Figure6:AverageQualityReductio
\label{Figure6:AverageQualityReduction}
\end{figure}
Results on both figures show that the proposed methods (i.e., \EXP, \EXPELTEN and \EXPELTWEN) are all able to outperform the reference \ac{hevc} for high \acs{plr}. In case of the proposed reference picture selection method (\EXP), quality gains in comparison with the \REF case are achieved for lower loss ratio, i.e., \acs{plr} as low as 2\% for all test conditions shown.
Results on both figures show that the proposed methods (\EXP, \EXPELTEN and \EXPELTWEN) are all able to outperform the reference \ac{hevc} for high \acs{plr}. In case of the proposed reference picture selection method (\EXP), quality gains in comparison with the \REF case are achieved for lower loss ratio, i.e., \acs{plr} as low as 2\% for all test conditions shown.
Comparing the results for both target bitrates also shows that the proposed methods are able to achieve higher quality gains for higher bitrates. Therefore, the for a lower bitrate (see results of Figure~\ref{Figure6:AverageQualityReduction}) the proposed methods only outperform the reference method for slightly higher \acs{plr}. This is more noticeable in the \EXPELTWEN case.
Summarising, the performance of the proposed methods is not similar across different video content and target bitrate, which impose a challenge on which method should be applied to achieve the highest decoded video quality in case of transmission errors. In order to achieve the highest quality the optimal trade-off between auxiliary information and video bitrate should be obtained by selecting the optimal error robust coding algorithm.