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- conclusion contributions proofread

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src/conclusion/contributions.tex
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In this thesis, we have presented three main contributions.
\paragraph{}
First, we set up a basic system allowing 3D navigation and 3D content streaming in the context of streaming online 3D content consisting in textured meshes.
First, we set up a basic system allowing navigation in a 3D scene (represented as a textured mesh) with the content being streamed through the network from a remote server.
We developed a navigation aid in the form of \textbf{3D bookmarks}, and we conducted a user study to analyse its impact on navigation and streaming.
On one hand, consistently with the state of the art, we observed that navigation aid \textbf{helps people navigating in a scene}, since they perform tasks faster and more easily.
On the other hand, we showed that benefiting from bookmarks in 3D navigation comes at the cost of a negative impact for the quality of service (QoS): since users navigate faster, they require more data during the same time span.
However, we also showed that this cost is not a fatality: using prior knowledge we have about bookmarks, we are able to \textbf{precompute data ordering offline} so that when users click on bookmark, their QoS improves.
On the other hand, we showed that benefiting from bookmarks in 3D navigation comes at the cost of a negative impact on the quality of service (QoS): since users navigate faster, they require more data during the same time span.
However, we also showed that this cost is not a fatality: using prior knowledge we have about bookmarks, we are able to \textbf{precompute an optimal data ordering offline} so that the QoS increases when users click on bookmarks.
Simulations on the traces we collected during the user study quantify how these precomputations \textbf{improve the QoS}.
This work has been published at the conference MMSys in 2016~\citep{bookmarks-impact}.
This work has been published at the ACM MMSys conference in 2016~\citep{bookmarks-impact}.
\paragraph{}
Then, we focus on the streaming aspect of the system.
The objective of this contribution is to introduce a system able to perform \textbf{scalable, view-dependent 3D streaming}.
This new framework proposes many improvements upon the basic system described in our first contribution: support for texture, moving computation from the server to the clients, support for multi-resolution textures, rendering performances considerations.
We took massive inspiration from the DASH technology, a standard for video streaming thanks to its scalability and its adaptability.
After studying the interactive aspect of 3D navigation, we proposed a contribution focusing on the streaming aspect of such a system.
The objective of this contribution wass to introduce a system able to perform \textbf{scalable, view-dependent 3D streaming}.
This new framework brings many improvements upon the basic system described in our first contribution: support for texture, externaliration of necessary computations from the server to the clients, support for multi-resolution textures, rendering performances considerations.
We drew massive inspiration from the DASH technology, a standard for video streaming used for its scalability and its adaptability.
We exploit the fact that DASH is made to be content agnostic to fit 3D content into its structure.
We used DASH-SRD extension to partition our 3D content tree and profit from this partition to perform view-dependant streaming, without having any computation to run on the server side.
For the clients, we implement loading policies based on a utility metric that gives a score for both geometry and texture portion of the model.
We throughly tested our solutions for different values of parameters, as well as for our different loading policies by running simulations, to propose an efficient framework that we name DASH-3D.
Following the path set by DASH-SRD, we propose to tile 3D content using a tree and encode this partition into a description file (MPD) to allow view-dependent streaming, without the need for computation on the server side.
On the client side, we implement loading policies that optimize a utility metric estimating how much geometry and texture segments contribute to the visual rendering of the scene at a particular viewpoint.
We thoroughly tested our solutions by running simulations with different parameter values, as well as different loading policies, to propose an efficient framework that we name DASH-3D.
This work has been published as a full paper at the conference ACMMM in 2018~\citep{dash-3d}.
A demo paper on the DASH-3D implementation was also published~\citep{dash-3d-demo}.
A demonstration paper on the DASH-3D implementation was also published~\citep{dash-3d-demo}.
\paragraph{}
Finally, we brought back the \textbf{3D navigation bookmark within DASH-3D}.
Finally, we brought back the \textbf{3D navigation bookmark within our DASH-3D framework}.
We developed interfaces that allow navigating in 3D scenes for both \textbf{desktop and mobile devices} and we reintroduced bookmarks in these interfaces.
The setup of our first contribution considered only geometry, triangle by triangle, which made precomputations and ordering straightforward.
Moreover, the server knows exactly the client needs, and thus create chunks adapted to the client's requirements.
Moreover, as the server knew exactly the client needs, it could create chunks adapted to the client's requirements.
In DASH-3D, the data is structured a priori (offline), so that chunks are grouped independently of a client's need.
However, this does not mean that all hope is lost: we are still able to precompute an optimal order for chunks from each bookmark, and, using the policies from our first contribution, switch to this optimal order when a user clicks a bookmark.
We therefore focus on precomputing an optimal order for chunks from each bookmark, and, alter the streaming policies from our second contribution to switch to this optimal order when a user clicks a bookmark.
Simulations show that the QoS is positively impacted by those policies.
A demo paper was published at the conference ACMMM in 2019~\citep{dash-3d-bookmarks-demo} showing the interfaces for desktop and mobile clients with bookmarks, but without the streaming aspect.
A demo paper was published at the conference ACMMM in 2019~\citep{dash-3d-bookmarks-demo} showing the interfaces for desktop and mobile clients with bookmarks, but without the streaming aspect. A journal paper will be submitted shortly to value this third contribution.

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src/plan.tex
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\frontmatter{}
\input{introduction/main}
%\input{introduction/main}
\resetstyle{}
\mainmatter{}
\input{foreword/main}
%\input{foreword/main}
\resetstyle{}
\input{state-of-the-art/main}
%\input{state-of-the-art/main}
\resetstyle{}
\input{preliminary-work/main}
%\input{preliminary-work/main}
\resetstyle{}
\input{dash-3d/main}
%\input{dash-3d/main}
\resetstyle{}
\input{system-bookmarks/main}
%\input{system-bookmarks/main}
\resetstyle{}
\backmatter{}