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Visibility acceleration for large-scale volume visualizationGao, Jinzhu 20 July 2004 (has links)
No description available.
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Real-time Visualization of Massive 3D Models on GPU Parallel ArchitecturesPeng, Chao 24 April 2013 (has links)
Real-time rendering of massive 3D models has been recognized as a challenging task due to the limited computational power and memory available in a workstation. Most existing acceleration techniques, such as mesh simplification algorithms with hierarchical data structures, suffer from the nature of sequential executions. As data complexity increases due to the fundamental advances in modeling and simulation technologies, 3D models become complex and require gigabytes in storage. Consequently, visualizing such large datasets becomes a computationally intensive process where sequential solutions are unable to satisfy the demands of real-time rendering.
Recently, the Graphics Processing Unit (GPU) has been praised as a massively parallel architecture not only for its significant improvements in performance but also because of its programmability for general-purpose computation. Today's GPUs allow researchers to solve problems by delivering fine-grained parallel implementations. In this dissertation, I concentrate on the design of parallel algorithms for real-time rendering of massive 3D polygonal models towards modern GPU architectures. As a result, the delivered rendering system supports high-performance visualization of 3D models composed of hundreds of millions of polygons on a single commodity workstation. / Ph. D.
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Revisitando o problema de visibilidade para visualiza??o tridimensionalCunha, Icaro Lins Leit?o da 22 January 2014 (has links)
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Previous issue date: 2014-01-22 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / 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 / N?s revisitamos o problema de visibilidade, que visa determinar um conjunto de primitivas potencialmente vis?veis em um conjunto de dados geom?tricos representados por
uma estrutura de dados, por exemplo uma malha de pol?gonos ou de tri?ngulos, propondo
uma solu??o para acelerar o processamento em aplica??es em visualiza??o tridimensional. Introduzimos uma estrutura enxuta, no sentido de abstra??o e redu??o de dados, que
pode ser usada para aplica??es online e interativas. O problema de visibilidade ? especialmente importante na visualiza??o 3D de cenas representadas por grande volume de
dados, em que n?o ? interessante manter todos os pol?gonos da cena em mem?ria. Isso
implicaria em um maior tempo gasto na renderiza??o, ou sendo at? mesmo imposs?vel
mant?-los todos em volumes imensos de dados. Nestes casos, dada uma posi??o e uma
dire??o de visualiza??o, o objetivo principal ? determinar e carregar o m?nimo poss?vel
de primitivas (pol?gonos) da cena, visando acelerar a etapa de renderiza??o. Para este
prop?sito, nosso algoritmo executa o corte de primitivas (culling) usando um paradigma
h?brido baseado em tr?s modelos conhecidos. A cena ? subdividida em c?lulas de uma
grade, sendo associada a cada uma dessas c?lulas as primitivas pertencentes a elas, e finalmente determinado o conjunto de primitivas potencialmente vis?veis. A novidade ? o
uso da triangula??o J
a
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para criar a subdivis?o em grade. Escolhemos esta estrutura devido
?s suas caracter?sticas relevantes de adaptatividade e algebrismo (facilidade de c?lculos).
Os resultados mostram uma melhoria substancial sobre os m?todos tradicionais quando
aplicados separadamente. O m?todo introduzido neste trabalho pode ser usado em dispositivos sem processador dedicado ou com baixo poder de processamento, e ainda, pode
ser utilizado para visualizar dados atrav?s da Internet, tal como em aplica??es de museus
virtuais
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