Some updates
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\bibliographystyle{abbrvnat}
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\setcitestyle{authoryear,open={[},close={]},citesep={,}}
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\usepackage{titling}
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\usepackage{multirow}
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\usepackage[colorlinks = true,
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linkcolor = blue,
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@ -69,7 +69,7 @@ Consider the piece of C++ code in Listings~\ref{f:undefined-behaviour-cpp} and~\
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\lstinputlisting[
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language=c++,
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label={f:undefined-behaviour-cpp},
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caption={Undefined behaviour: with for each syntax}
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caption={Undefined behaviour with for each syntax}
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]{assets/dash-3d-implementation/undefined-behaviour.cpp}
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\lstinputlisting[
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language=c++,
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17
src/main.tex
17
src/main.tex
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@ -38,18 +38,19 @@
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\quad\\
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This version was compiled on \today{} at \currenttime{}.
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\makeflyleaf{}
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\begin{titlepage}
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\begin{tikzpicture}[overlay,remember picture,line width=5pt]
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\node at (current page.center) {\includegraphics[width=\pagewidth]{assets/background.png}};
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\node at (current page.south) [%
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draw=red,
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\node at (12, -22) [%
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inner sep=15pt,
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fill=white,
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above=5cm,
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font=\sffamily\bfseries\Huge
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] {The book title};
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thin,
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draw=MidnightBlue,
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fill=black,
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font=\sffamily\bfseries\Huge,
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align=left,
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fill opacity=0.7,
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text opacity=1,
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] {\color{white}\thetitle\\\color{white}\LARGE\theauthor};
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\end{tikzpicture}
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\end{titlepage}
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@ -0,0 +1,9 @@
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\fresh{}
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\section{Conclusion}
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In this chapter, our objective was to propose a mobile interface for DASH-3D and to integrate back the interaction aspects that we developed in Chapter~\ref{bi}.
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We have seen that doing so is not trivial, and many improvements have been made.
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For aesthetics and performance reasons, the UI of the bookmarks have been changed.
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We developed an algorithm that computes offline the optimal order of segments from a certain viewpoint.
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We encoded this optimal order in a JSON file and we modified our MPD in order to give metadata about bookmarks to the client and we modified our client to benefit from this.
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We then conducted a user study on 18 participants where users had to navigate in scenes with bookmarks and using various streaming policies.
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The results seem to indicate that users prefer the optimized version of the policy, which is coherent with the PSNR values that we computed.\todo{this conclusion is real real bad}
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@ -11,3 +11,6 @@
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\input{system-bookmarks/user-study}
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\resetstyle{}
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\input{system-bookmarks/conclusion}
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\resetstyle{}
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@ -23,7 +23,7 @@ The experiment consists in 4 phases: a tutorial, a comparison between interfaces
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The experiment starts with a tutorial, so the users can get accustomed to our interface.
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This tutorial shows the different types of interactions available and explains how to use them.
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\paragraph{Bookmarks}
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\paragraph{Bookmark path}
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This part of the experiment consists in two 1 minute long sessions: the first one has a naked interface where the only available intarctions are translations and rotations of the camera, and the second one enhances the interface with bookmarks.
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There are no special tasks other than to take a walk around the model.
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@ -79,11 +79,23 @@ We could argue that they do not like the bookmarks because they make the task to
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Among the 18 participants of this user study, 10 confirmed that they preferred the optimized policy, 4 preferred the greedy policy, and 4 did not perceive the difference.
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Another interesting fact is that on the last part of the experiment (the free navigation) the average number of clicks on bookmarks is 3 for users having the greedy policy and 5.3 for users having the optimized policy.
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Even though statistical significance is not reached, this result seems to indicate that a policy optimized for bookmarks could lead users to click more on bookmarks.
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\subsubsection{Quantitative results}
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By collecting all the traces during the experiments, we are able to replay the rendering and evaluate the PSNR that users saw during their experiment.
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% Figure~\ref{sb:psnr-second-experiment}
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Figure~\ref{sb:psnr-second-experiment} shows the average PSNR that user got while navigating during the second experiment (bookmark path).
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Below the PSNR curve is a curve that shows how many users were moving to or staying at a bookmark position.
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As we can see, the two policies perform in the same way in the beginning when few users are moving to a bookmarks.
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However, when they start clicking on bookmarks, the gap grows and our optimized policy perform better.
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Figure~\ref{sb:psnr-second-experiment-after-click} shows the PSNR after a click on a bookmark.
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To compute these curves, we isolated the ten seconds after each click on a bookmark that occurs and we averaged them all.
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These curves isolate the effect of our optimized policy, and shows the difference a user can feel when clicking on a bookmark.
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Figures~\ref{sb:psnr-third-experiment} and~\ref{sb:psnr-third-experiment-after-click} represent the same curves on the third experiment (free navigation).
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On average, the difference in terms of PSNR is less obvious, and both strategies seem to perform the same way.
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This may be due to the lower number of users clicking on bookmarks.
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However, Figure~\ref{sb:psnr-third-experiment-after-click} is clear: the optimized policy performs way better after a click on a bookmark.
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\begin{figure}[th]
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\centering
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