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Thomas Forgione
2019-10-14 15:03:28 +02:00
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src/introduction/challenges.tex
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\section{Open problems\label{i:challenges}}
The objective of our work is to design a system that allows a user to access remote 3D content and that guarantees good quality of service and quality of experience.
The objective of our work is to design a system that allows a user to access remote 3D content and that guarantees both good quality of service and good quality of experience.
A 3D streaming client has lots of tasks to accomplish:
\begin{itemize}
\item render a scene;
\item find out what to download and download it;
\item find out what part of the model to download next;
\item download the next part;
\item parse the downloaded content;
\item add the parsed result to the scene;
\item manage the interaction with the user.
@@ -19,25 +20,26 @@ This opens multiple problems that we need to take care of.
% Any preprocessing that can be done on our 3D data gives us a strategical advantage since it consists in computations that will not be needed live, neither for the server nor for the client.
% Furthermore, for streaming, data needs to be split into chunks that are requested separately, so perparing those chunks in advance can also help the streaming.
Before streaming content, it needs to be prepared.
The segmentation of the content into chunks is particularly important for streaming since it allows transmitting only a portion of the data to the client, that it can render before downloading more chunks.
The segmentation of the content into chunks is particularly important for streaming since it allows transmitting only a portion of the data to the client.
A partial model consisting in the downloaded content, it can be rendered before downloading more chunks.
Content preparation also includes compression.
One of the questions this thesis has to answer is \emph{``what is the best way to prepare 3D content so that a client can benefit from it?''}
One of the questions this thesis has to answer is: \emph{what is the best way to prepare 3D content so that a client can progressively download and render the 3D model?}
\paragraph{Streaming policies.}
Once our content is prepared and split in chunks, a client needs to determine which chunks it needs to download.
A chunk that contains data in the field of view of the user is more relevant than a chunk outside of it; a chunk that is close to the camera is more relevant than a chunk far away from the camera, etc.
Once our content is prepared and split in chunks, a client needs to determine which chunks should be downloaded first.
A chunk that contains data in the field of view of the user is more relevant than a chunk that is not inside; a chunk that is close to the camera is more relevant than a chunk far away from the camera, etc.
This should also include other contextual parameters, such as the size of a chunk, the bandwidth, the user's behaviour, etc.
The most important question we have to answer is \emph{how to determine which chunks need to be downloaded depending on the chunks themselves and the user's interactions?}
The most important questions we have to answer are: \emph{how to estimate a chunk utility, and how to determine which chunks need to be downloaded depending on the chunks themselves and the user's interactions?}
\paragraph{Evaluation.}
In such systems, the two most important criteria for evaluation are quality of service, and quality of experience.
The quality of service is a network-centric metric, which considers values such as throughput.
The quality of experience is a user-centric metric, and can only be measured by asking how users feel about a system.
To be able to know which streaming policies are best, one needs to know \emph{how to compare streaming policies and evalute the impact of their parameters in terms of quality of service and quality of experience?}
To be able to know which streaming policies are best, one needs to know \emph{how to compare streaming policies and evaluate the impact of their parameters in terms of quality of service and quality of experience?}
\paragraph{Implementation.}
The objective of our work is to setup a client-server architecture that answers the problems mentioned earlier (content preparation, chunk utility, streaming policies).
In this regard, we have to find out \emph{how do we build this architecture while keeping the computational load on the server low so it can scale and the client efficient so that it has resources to perform its many tasks?}
The objective of our work is to setup a client-server architecture that answers the above problems: content preparation, chunk utility, streaming policies.
In this regard, we have to find out \emph{how do we build this architecture that keeps the computational load for the server low so it scales up and for the client so that it has enough resources to perform the tasks described above?}
% This implementation must respect constraints required for performant software:
%

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src/introduction/main.tex
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During the last years, 3D acquisition and modeling techniques have progressed a lot.
Recent software such as \href{https://alicevision.org/\#meshroom}{Meshroom} use \emph{structure from motion} and \emph{multi view stereo} to infer a 3D model from a set of photographs.
There are more and more devices that are specifically built to obtain 3D data: some are more expensive and provide with very precise information such as Lidar, and some cheaper devices can obtain coarse data such as the Kinect.
There are more and more devices that are specifically built to obtain 3D data: some are more expensive and provide with very precise information such as LIDAR (Light Detection And Ranging, as in RADAR but with light instead of radio waves), and some cheaper devices can obtain coarse data such as the Kinect.
Thanks to these techniques, more and more 3D data become available.
These models have potential for multiple purposes, for example, they can be 3D printed, which can reduce the production cost of some pieces of hardware or enable the creation of new objects, but most uses will consist in visualisation.
For example, they can be used for augmented reality, to provide user with feedback that can be useful to help worker with complex tasks, but also for fashion (for example, \emph{Fitting Box} is a company that develops software to virtually try glasses).
3D acquisition and visualisation is also useful to preserve cultural heritage, and software such as Google Heritage or 3DHop are such examples, or to allow users navigating in a city (as in Google Earth or Google Maps in 3D).
\href{https://sketchfab.com}{Sketchfab} is an example of a website allowing users to share their 3D models and visualise models from other users.
In most 3D visualisation systems, the 3D data needs to be transmitted to a terminal before the user can visualise it.
The improvements in the acquisition setups we described lead to an increasing quality of the 3D models, and an increasing size in bytes as well.
Simply downloading 3D content and waiting until the content is fully downloaded to let the user visualise it is no longer a satisfactory solution, and streaming needs to be performed.
In this thesis, we are especially interested in the navigation and in the streaming of large 3D scenes, such as districts or whole cities.
In most 3D visualisation systems, the 3D data is stored on a server and needs to be transmitted to a terminal before the user can visualise it.
The improvements in the acquisition setups we described lead to an increasing quality of the 3D models, thus an increasing size in bytes as well.
Simply downloading 3D content and waiting until the content is fully downloaded to let the user visualise it is no longer a satisfactory solution, so streaming needs to be performed.
In this thesis, we propose a full framework for the navigation and the streaming of large 3D scenes, such as districts or whole cities.
% With the progress in data acquisition and modeling techniques, networked virtual environments, or NVE, are increasing in scale.
% For instance,~\cite{urban-data-visualisation} reported that the 3D scene for the city of Lyon takes more than 30 GB of data.

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src/introduction/outline.tex
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\section{Thesis outline}
First, in Chapter~\ref{f}, we give some preliminary information required to understand the types of objects we are manipulating in this thesis.
We then proceed to compare 3D and video content: surprisingly, video and 3D share many problems, and analysing them gives inspiration for building a 3D streaming system.
We then proceed to compare 3D and video content: surprisingly, video and 3D share many features, and analysing video setting gives inspiration for building a 3D streaming system.
In Chapter~\ref{sote}, we present a review of the state of the art in the multimedia interaction and streaming.
This chapter starts with an analysis of the video streaming standards.
Then it reviews the different manners of performing 3D streaming.
Then it reviews the different 3D streaming approaches.
The last section of this chapter focuses on 3D interaction.
Then, in Chapter~\ref{bi}, we present our first contribution: an in-depth analysis of the impact of the UI on navigation and streaming in a 3D scene.
We first develop a basic interface for navigating in 3D and we introduce 3D objects called \emph{bookmarks} that help users navigating in the scene.
We then present a user study that we conducted on 50 people that shows that bookmarks have a great impact on how easy it is for a user to perform tasks such as finding objects.
We first develop a basic interface for navigating in 3D and thus, we introduce 3D objects called \emph{bookmarks} that help users navigating in the scene.
We then present a user study that we conducted on 50 people that shows that bookmarks ease user navigation as bookmark improves performance at tasks such as finding objects.
% Then, we setup a basic 3D streaming system that allows us to replay the traces collected during the user study and simulate 3D streaming at the same time.
We analyse how the presence of bookmarks impacts the streaming, and we propose and evaluate a few streaming policies that rely on pre-computations that can be made thanks to bookmarks and that can increase the quality of experience.
We analyse how the presence of bookmarks impacts the streaming: we propose and evaluate streaming policies based on pre-computations relying on bookmarks and that measurably increase the quality of experience.
In Chapter~\ref{d3}, we present the most important contribution of this thesis: DASH-3D.
DASH-3D is an adaptation of the video streaming standard to 3D streaming.
DASH-3D is an adaptation of DASH (Dynamic Adaptive Streaming over HTTP): the video streaming standard, to 3D streaming.
We first describe how we adapt the concepts of DASH to 3D content, including the segmentation of content.
We then define utility metrics that associate score to each chunk depending on the camera's position.
We then define utility metrics that associate score to each chunk depending on the user's position.
Then, we present a client and various streaming policies based on our utilities that can benefit from the DASH format.
We finally evaluate the different parameters of our client.