\section{Future work}

Successfully adapting the DASH framework to 3D content is a significant step that naturally opens many exciting perspectives.
In this section, we shall detail three major perspectives for future work.

\subsection{Semantic information}

In this thesis, no attention has been given to semantic.
Our content preparation considers only spatial information both for 3D content and clients so our adaptation sets and segments may separate data that could be grouped semantically.
Having semantic information could help us derive a better structure for our content: we know for example that displaying half a building will lead to low quality of experience.
In order to account for semantic besides partitioning, we could also adapt the utilities we have been defining for our segments: some semantically significant data can be considered as more important than other by taking it into account in our utilities.

\subsection{Compression / multi-resolution for geometry}

In this thesis, we considered different resolutions for textures, but we have not investigated geometry compression nor multi-resolution.
Geometry data is transmitted as OBJ files (mostly consisting in ASCII encoded numbers), which is terrible for transmission.
Compression would reduce the size of the geometry files, thus increasing the quality of experience.
Supporting multi-resolution geometry would improve it even more, even if performing multi-resolution on a large and heterogeneous scene is difficult.
To this day, only little attention has been given to multi-resolution compression for textured geometry~\citep{maglo20153d}, and their focus has been on 3D objects.
Once again, semantic information could be a great help in this regard.
Other compression schemes are also interesting for our framework: \citep{demir2016proceduralization} describes an algorithm to proceduralize architectural models, and the authors also propose a semi-automatic method in \citep{demir2018guided} to give some control to models editors.
Compressing cities through this process can greatly increase the quality of service of our framework.


\subsection{Performance optimization}
Performance has already been discussed in Chapter~\ref{d3}.
However in this thesis, we have for example never discussed removing data from the media engine when it is no longer useful.
This means that on a really large scene, performance is bound to become damaged due to the growing amount of data to render, and the saturation of GPU memory.
In order for a client (even more a mobile client) to be able to support such scenes, it is necessary to implement a mechanism to periodically free the memory.
The utility measures that we described in Section~\ref{d3:utility} are good candidates to determine what to unload.
We could estimate the performance of our system by measuring variables such as memory used or framerate and use those values to discard data with low enough utility.

Finally, this thesis has proposed a first, but ambitious, complete development of a DASH-3D framework, providing a scalable, efficient, streaming for textured meshes.
This framework can be directly used to adapt to semantic or compressed geometry.
As the client, especially for mobile clients, special attention is needed for handling locally the large amount of received data for a controlled framerate.
