deletions | additions       diff --git a/section_Datasets_to_follow_up__.tex b/section_Datasets_to_follow_up__.tex  index d12ea28..9f049f2 100644  --- a/section_Datasets_to_follow_up__.tex  +++ b/section_Datasets_to_follow_up__.tex 
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\section{Datasets to follow up}  report the existing datasets through a table and their possible usage and location  In this context, one crucial aspect is the presence of only a small number of datasets that can be used for quality assessment in the field of FTV. More specifically ...... A list of available datasets is presented here below while a summary of the main characteristics of these datasets is in Table \ref{tab:datasets}:  \begin{itemize}  \item DIBR Images \cite{DIBRImage}: three multiview plus depth (MVD) sequences are considered: Book Arrival (1024x768 pixels, 16 cameras with 6.5 cm spacing), Lovebird1 (1024x768 pixels, 12 cameras with 3.5 cm spacing) and Newspaper (1024x768 pixels, 9 cameras with 5 cm spacing). Seven DIBR algorithms are used to create for each sequence four new viewpoints. From the created sequences, key frames are extracted and included in the dataset. Absolute Category Rating (ACR) and pair comparison have been used for Mean Opinion Score (MOS) collection. 
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Free-Viewpoint synthesized videos & 264 video sequences & MOS & yes\\ \hline  High-Quality Streamable Free-Viewpoint Video \cite{Collet_2015}& & no & yes \\ \hline  \end{tabular}  \caption{Characteristics of the available datasets in the state-of-the-art.}  \label{tab:datasets}  \end{center}