671 research outputs found
Task-based adaptive multiresolution for time-space multi-scale reaction-diffusion systems on multi-core architectures
A new solver featuring time-space adaptation and error control has been
recently introduced to tackle the numerical solution of stiff
reaction-diffusion systems. Based on operator splitting, finite volume adaptive
multiresolution and high order time integrators with specific stability
properties for each operator, this strategy yields high computational
efficiency for large multidimensional computations on standard architectures
such as powerful workstations. However, the data structure of the original
implementation, based on trees of pointers, provides limited opportunities for
efficiency enhancements, while posing serious challenges in terms of parallel
programming and load balancing. The present contribution proposes a new
implementation of the whole set of numerical methods including Radau5 and
ROCK4, relying on a fully different data structure together with the use of a
specific library, TBB, for shared-memory, task-based parallelism with
work-stealing. The performance of our implementation is assessed in a series of
test-cases of increasing difficulty in two and three dimensions on multi-core
and many-core architectures, demonstrating high scalability
A Hierarchical Triangulation for Multiresolution Terrain Models
Interactive visualisation of triangulated terrain surfaces is still a problem for virtual reality systems. A polygonal model of very large terrain data requires a large number of triangles. The main problems are the representation rendering efficiency and the transmission over networks. The major challenge is to simplify a model while preserving its appearance. A multiresolution model represents different levels of detail of an object. We can choose the preferable level of detail according to the position of the observer to improve rendering and we can make a progressive transmission of the different levels. We propose a multiresolution triangulation scheme that eliminates the restrictions of the restricted quadtree triangulation and obtains better results.Facultad de Informátic
Cached Geometry Manager for View-dependent LOD Rendering
The new generation of commodity graphics cards with significant on-board video memory has become widely
popular and provides high-performance rendering and flexibility. One of the features to be exploited with this
hardware is the use of the on-board video memory to store geometry information. This strategy significantly
reduces the data transfer overhead from sending geometry data over the (AGP) bus interface from main memory
to the graphics card. However, taking advantage of cached geometry is not a trivial task because the data models
often exceed the memory size of the graphics card. In this paper we present a dynamic Cached Geometry
Manager (CGM) to address this issue. We show how this technique improves the performance of real-time
view-dependent level-of-detail (LOD) selection and rendering algorithms of large data sets. Alternative caching
approaches have been analyzed over two different view-dependent progressive mesh (VDPM) frameworks: one
for rendering of arbitrary manifold 3D meshes, and one for terrain visualization
Survey of semi-regular multiresolution models for interactive terrain rendering
Rendering high quality digital terrains at interactive rates requires carefully crafted algorithms and data structures able to balance the competing requirements of realism and frame rates, while taking into account the memory and speed limitations of the underlying graphics platform. In this survey, we analyze multiresolution approaches that exploit a certain semi-regularity of the data. These approaches have produced some of the most efficient systems to date. After providing a short background and motivation for the methods, we focus on illustrating models based on tiled blocks and nested regular grids, quadtrees and triangle bin-trees triangulations, as well as cluster-based approaches. We then discuss LOD error metrics and system-level data management aspects of interactive terrain visualization, including dynamic scene management, out-of-core data organization and compression, as well as numerical accurac
3D Mesh Simplification. A survey of algorithms and CAD model simplification tests
Simplification of highly detailed CAD models is an important step when CAD
models are visualized or by other means utilized in augmented reality applications.
Without simplification, CAD models may cause severe processing and storage is-
sues especially in mobile devices. In addition, simplified models may have other
advantages like better visual clarity or improved reliability when used for visual pose
tracking. The geometry of CAD models is invariably presented in form of a 3D
mesh. In this paper, we survey mesh simplification algorithms in general and focus
especially to algorithms that can be used to simplify CAD models. We test some
commonly known algorithms with real world CAD data and characterize some new
CAD related simplification algorithms that have not been surveyed in previous mesh
simplification reviews.Siirretty Doriast
GPU-based Streaming for Parallel Level of Detail on Massive Model Rendering
Rendering massive 3D models in real-time has long been recognized as a very challenging problem because of the limited computational power and memory space available in a workstation. Most existing rendering techniques, especially level of detail (LOD) processing, have suffered from their sequential execution natures, and does not scale well with the size of the models. We present a GPU-based progressive mesh simplification approach which enables the interactive rendering of large 3D models with hundreds of millions of triangles. Our work contributes to the massive rendering research in two ways. First, we develop a novel data structure to represent the progressive LOD mesh, and design a parallel mesh simplification algorithm towards GPU architecture. Second, we propose a GPU-based streaming approach which adopt a frame-to-frame coherence scheme in order to minimize the high communication cost between CPU and GPU. Our results show that the parallel mesh simplification algorithm and GPU-based streaming approach significantly improve the overall rendering performance
Deformable Multisurface Segmentation of the Spine for Orthopedic Surgery Planning and Simulation
Purpose: We describe a shape-aware multisurface simplex deformable model for the segmentation of healthy as well as pathological lumbar spine in medical image data.
Approach: This model provides an accurate and robust segmentation scheme for the identification of intervertebral disc pathologies to enable the minimally supervised planning and patient-specific simulation of spine surgery, in a manner that combines multisurface and shape statistics-based variants of the deformable simplex model. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection of the pathological region, user assistance is allowed to disable the prior shape influence during deformation.
Results: Results demonstrate validation against user-assisted expert segmentation, showing excellent boundary agreement and prevention of spatial overlap between neighboring surfaces. This section also plots the characteristics of the statistical shape model, such as compactness, generalizability and specificity, as a function of the number of modes used to represent the family of shapes. Final results demonstrate a proof-of-concept deformation application based on the open-source surgery simulation Simulation Open Framework Architecture toolkit.
Conclusions: To summarize, we present a deformable multisurface model that embeds a shape statistics force, with applications to surgery planning and simulation
AMM: Adaptive Multilinear Meshes
We present Adaptive Multilinear Meshes (AMM), a new framework that
significantly reduces the memory footprint compared to existing data
structures. AMM uses a hierarchy of cuboidal cells to create continuous,
piecewise multilinear representation of uniformly sampled data. Furthermore,
AMM can selectively relax or enforce constraints on conformity, continuity, and
coverage, creating a highly adaptive and flexible representation to support a
wide range of use cases. AMM supports incremental updates in both spatial
resolution and numerical precision establishing the first practical data
structure that can seamlessly explore the tradeoff between resolution and
precision. We use tensor products of linear B-spline wavelets to create an
adaptive representation and illustrate the advantages of our framework. AMM
provides a simple interface for evaluating the function defined on the adaptive
mesh, efficiently traversing the mesh, and manipulating the mesh, including
incremental, partial updates. Our framework is easy to adopt for standard
visualization and analysis tasks. As an example, we provide a VTK interface,
through efficient on-demand conversion, which can be used directly by
corresponding tools, such as VisIt, disseminating the advantages of faster
processing and a smaller memory footprint to a wider audience. We demonstrate
the advantages of our approach for simplifying scalar-valued data for commonly
used visualization and analysis tasks using incremental construction, according
to mixed resolution and precision data streams
A Hierarchical Triangulation for Multiresolution Terrain Models
Interactive visualisation of triangulated terrain surfaces is still a problem for virtual reality systems. A polygonal model of very large terrain data requires a large number of triangles. The main problems are the representation rendering efficiency and the transmission over networks. The major challenge is to simplify a model while preserving its appearance. A multiresolution model represents different levels of detail of an object. We can choose the preferable level of detail according to the position of the observer to improve rendering and we can make a progressive transmission of the different levels. We propose a multiresolution triangulation scheme that eliminates the restrictions of the restricted quadtree triangulation and obtains better results.Facultad de Informátic
Doctor of Philosophy
dissertationShape analysis is a well-established tool for processing surfaces. It is often a first step in performing tasks such as segmentation, symmetry detection, and finding correspondences between shapes. Shape analysis is traditionally employed on well-sampled surfaces where the geometry and topology is precisely known. When the form of the surface is that of a point cloud containing nonuniform sampling, noise, and incomplete measurements, traditional shape analysis methods perform poorly. Although one may first perform reconstruction on such a point cloud prior to performing shape analysis, if the geometry and topology is far from the true surface, then this can have an adverse impact on the subsequent analysis. Furthermore, for triangulated surfaces containing noise, thin sheets, and poorly shaped triangles, existing shape analysis methods can be highly unstable. This thesis explores methods of shape analysis applied directly to such defect-laden shapes. We first study the problem of surface reconstruction, in order to obtain a better understanding of the types of point clouds for which reconstruction methods contain difficulties. To this end, we have devised a benchmark for surface reconstruction, establishing a standard for measuring error in reconstruction. We then develop a new method for consistently orienting normals of such challenging point clouds by using a collection of harmonic functions, intrinsically defined on the point cloud. Next, we develop a new shape analysis tool which is tolerant to imperfections, by constructing distances directly on the point cloud defined as the likelihood of two points belonging to a mutually common medial ball, and apply this for segmentation and reconstruction. We extend this distance measure to define a diffusion process on the point cloud, tolerant to missing data, which is used for the purposes of matching incomplete shapes undergoing a nonrigid deformation. Lastly, we have developed an intrinsic method for multiresolution remeshing of a poor-quality triangulated surface via spectral bisection
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