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@ -812,3 +812,12 @@
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year={2015},
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publisher={ACM}
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}
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@inproceedings{portaneri2019cost,
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title={Cost-driven framework for progressive compression of textured meshes},
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author={Portaneri, C{\'e}dric and Alliez, Pierre and Hemmer, Michael and Birklein, Lukas and Schoemer, Elmar},
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booktitle={Proceedings of the 10th ACM Multimedia Systems Conference},
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pages={175--188},
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year={2019},
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organization={ACM}
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}
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@ -29,7 +29,7 @@ Such viewpoints can be either static, or dynamically adapted:~\citep{dual-mode-u
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\begin{figure}[ht]
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\centering
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\includegraphics[width=0.5\textwidth]{assets/state-of-the-art/3d-interaction/burtnyk.png}
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\includegraphics[width=0.7\textwidth]{assets/state-of-the-art/3d-interaction/burtnyk.png}
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\caption{Screenshot of an interface with menu for navigation~\citep{showmotion}}
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\end{figure}
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@ -81,6 +81,12 @@ After content preparation, the mesh consists in a base mesh and a sequence of pa
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Thus, a client can start by downloading the base mesh, display it to the user, and keep downloading refinement operations (vertex splits) and display details as time goes by.
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This process reduces the time a user has to wait before seeing something, thus increases the quality of experience.
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\begin{figure}[ht]
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\centering
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\includegraphics[width=\textwidth]{assets/state-of-the-art/3d-streaming/progressivemesh.png}
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\caption{Four levels of resolution of a mesh~\citep{progressive-meshes}}
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\end{figure}
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These methods have been vastly researched \citep{bayazit20093,mamou2010shape}, but very few of these methods can handle meshes with attributes, such as texture coordinates.
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\citep{streaming-compressed-webgl} develop a dedicated progressive compression algorithm based on iterative decimation, for efficient decoding, in order to be usable on web clients.
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@ -133,6 +139,12 @@ Even though there are no associated publications, it seems that the interface do
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The choice of the nearby can be based based on an a priori, discretized, partitioned version of the environment; for example, \citep{3d-tiles} developed 3D Tiles, is a specification for visualizing massive 3D geospatial data developed by Cesium and built on top of glTF\@.
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Their main goal is to display 3D objects on top of regular maps.
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\begin{figure}[ht]
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\centering
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\includegraphics[width=0.8\textwidth]{assets/state-of-the-art/3d-streaming/3dtiles.png}
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\caption{Screenshot of 3D Tiles interface~\citep{3d-tiles}}
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\end{figure}
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\subsection{Geometry and textures}
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As discussed in Chapter~\ref{f:3d}, most 3D scenes consists in two main types of data: geometry and textures.
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@ -143,7 +155,7 @@ Their approaches combine the distortion caused by having lower resolution meshes
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\citep{progressive-compression-textured-meshes} also deals with the geometry / texture compromise.
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This work designs a cost driven framework for 3D data compression, both in terms of geometry and textures.
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This framework generates an atlas for textures that enables efficient compression and multiresolution scheme.
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All four works considered a single, manifold textured mesh model with progressive meshes, and is not applicable in our work since we deal with large scenes with autointersections and T vertices.
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All four works considered a single, manifold textured mesh model with progressive meshes, and are not applicable in our work since we deal with large scenes with autointersections and T vertices.
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Regarding texture streaming, \citep{simon2019streaming} propose a way to stream a set of textures by encoding the textures into a video.
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Each texture is segmented into tiles of a fixed size.
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