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Thomas Forgione
2019-10-08 16:04:12 +02:00
parent 89edf5fc03
commit 3006fd5f98
6 changed files with 37 additions and 11 deletions
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src/system-bookmarks/conclusion.tex Normal file
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\fresh{}
\section{Conclusion}
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}.
We have seen that doing so is not trivial, and many improvements have been made.
For aesthetics and performance reasons, the UI of the bookmarks have been changed.
We developed an algorithm that computes offline the optimal order of segments from a certain viewpoint.
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.
We then conducted a user study on 18 participants where users had to navigate in scenes with bookmarks and using various streaming policies.
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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src/system-bookmarks/main.tex
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\input{system-bookmarks/user-study}
\resetstyle{}
\input{system-bookmarks/conclusion}
\resetstyle{}

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src/system-bookmarks/user-study.tex
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The experiment starts with a tutorial, so the users can get accustomed to our interface.
This tutorial shows the different types of interactions available and explains how to use them.
\paragraph{Bookmarks}
\paragraph{Bookmark path}
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.
There are no special tasks other than to take a walk around the model.
@@ -79,11 +79,23 @@ We could argue that they do not like the bookmarks because they make the task to
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.
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.
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.
\subsubsection{Quantitative results}
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.
% Figure~\ref{sb:psnr-second-experiment}
Figure~\ref{sb:psnr-second-experiment} shows the average PSNR that user got while navigating during the second experiment (bookmark path).
Below the PSNR curve is a curve that shows how many users were moving to or staying at a bookmark position.
As we can see, the two policies perform in the same way in the beginning when few users are moving to a bookmarks.
However, when they start clicking on bookmarks, the gap grows and our optimized policy perform better.
Figure~\ref{sb:psnr-second-experiment-after-click} shows the PSNR after a click on a bookmark.
To compute these curves, we isolated the ten seconds after each click on a bookmark that occurs and we averaged them all.
These curves isolate the effect of our optimized policy, and shows the difference a user can feel when clicking on a bookmark.
Figures~\ref{sb:psnr-third-experiment} and~\ref{sb:psnr-third-experiment-after-click} represent the same curves on the third experiment (free navigation).
On average, the difference in terms of PSNR is less obvious, and both strategies seem to perform the same way.
This may be due to the lower number of users clicking on bookmarks.
However, Figure~\ref{sb:psnr-third-experiment-after-click} is clear: the optimized policy performs way better after a click on a bookmark.
\begin{figure}[th]
\centering