Revisitando o problema de visibilidade para visualização tridimensional
We revisit the problem of visibility, which is to determine a set of primitives potentially visible in a set of geometry data represented by a data structure, such as a mesh of polygons or triangles, we propose a solution for speeding up the three-dimensional visualization processing in applications...
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| Formaat: | doctoralThesis |
| Taal: | por |
| Gepubliceerd in: |
Universidade Federal do Rio Grande do Norte
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| Online toegang: | https://repositorio.ufrn.br/jspui/handle/123456789/15250 |
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| Samenvatting: | We revisit the problem of visibility, which is to determine a set of primitives potentially visible in a set of geometry data represented by a data structure, such as a mesh
of polygons or triangles, we propose a solution for speeding up the three-dimensional
visualization processing in applications. We introduce a lean structure , in the sense of
data abstraction and reduction, which can be used for online and interactive applications.
The visibility problem is especially important in 3D visualization of scenes represented
by large volumes of data, when it is not worthwhile keeping all polygons of the scene in
memory. This implies a greater time spent in the rendering, or is even impossible to keep
them all in huge volumes of data. In these cases, given a position and a direction of view,
the main objective is to determine and load a minimum ammount of primitives (polygons)
in the scene, to accelerate the rendering step. For this purpose, our algorithm performs
cutting primitives (culling) using a hybrid paradigm based on three known techniques.
The scene is divided into a cell grid, for each cell we associate the primitives that belong
to them, and finally determined the set of primitives potentially visible. The novelty is
the use of triangulation Ja
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to create the subdivision grid. We chose this structure because of its relevant characteristics of adaptivity and algebrism (ease of calculations). The results show a substantial improvement over traditional methods when applied separately. The method introduced in this work can be used in devices with low or no dedicated processing power CPU, and also can be used to view data via the Internet, such as virtual
museums applications |
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