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Well designed data structures and access methods are vital to developing efficient visualization algorithms. The cell structure is a compact, general data structure for representing ndimensional topological constructs such as unstructured grids, polygonal, or triangle strip representations. The cell structure also provides constant time access meth...
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... There has been a substantial amount of research invested in developing efficient vertex removal algorithms [15]. Initially, Schroeder and Yamrom [19] proposed an algorithm for decimating manifold surfaces. Each vertex removal consists of deleting all triangles connected to a vertex and triangulating the boundary loop left by the removed triangles. ...
In this paper we present a GPU-based method for removing shape details of 3D models. 3D models used in finite element analysis (FEA) are often either constructed for the purpose of manufacturing, or a result of 3D scanning. The models therefore contain shape details that are neither important for FEA nor compatible with the mechanical hypotheses. Vertex removal is a popular method for removing geometrical details where vertices are removed one by one, provided certain constraints are satisfied. The constraints can either be based purely on geometrical properties, or also on mechanical ones. The computations required in this process can be time consuming, especially if mechanical constraints are involved. The main idea behind our method is to perform the computations for all the vertices in parallel using graphics hardware, and then use the CPU to maintain the data structure representing the triangulation. As a result, simplification functions can stay interactive while incorporating complementary mechanically-based criteria in addition to the geometric ones involved in shape transformation.
... Schroeder and Yamrom [91] present a data structure for efficient visualization algorithms. This structure is a variation of display lists with additional hierarchical information. ...
The main focus of the research presented in this dissertation is real-time visualization of large photo-realistic models created from multimodal data sets. These models are derived from range and intensity data acquired from a laser range camera along with color, thermal, or radiation data from the scene. The capability to maintain a constant display rate when dealing with these large models is desired in addition to the ability for multiple users to interact with the data. A 3D virtual reality environment is perfect for interaction with and visualization of the models created from the data sets that have been acquired. To achieve our goal, a tool for visualization consisting of both hardware and software is designed and implemented. The hardware is based around the concept of a CAVE system comprised of a large screen and several projectors. The hardware setup employed is known as the MERLIN (Multi-usER Low-cost INtegrated) visualization system. This includes a desktop SGI computer driving three VGA projectors which display onto a custom-built screen along with several VR interface devices. To maintain a constant display rate, since the number of triangles that a specific machine can draw each second is fixed, a means by which the number of triangles can be adjusted is needed. This requires both a reduction method and a multiresolution representation. The multiresolution modeling technique that is presented is a pattern vector based technique known as POLYMUR (POLYgon MUltimodal Reduction) which is capable of handling the multimodal data sets. This method outputs a multiresolution file which can be used to automatically select the proper resolution needed to maintain the user's desired frame rate when interacting with the model and fill in the details when the model is ...
... Their paper demonstrated simplifications of models containing as many as 1,700,000 triangles. The computation time to simplify a model of n = 400, 000 vertices to m = 40, 000 vertices is about 14 minutes on an R4000 processor [115]. This method uses significant memory, like Lee's. ...
... This method uses significant memory, like Lee's. To conserve memory, compact data structures were developed [115]. Source code for this algorithm is available [114]. ...
This paper surveys methods for simplifying and approximating polygonal surfaces. A polygonal surface is a piecewiselinear surface in 3-D defined by a set of polygons; typically a set of triangles. Methods from computer graphics, computer vision, cartography, computational geometry, and other fields are classified, summarized, and compared both practically and theoretically. The surface types range from height fields (bivariate functions), to manifolds, to nonmanifold self-intersecting surfaces. Piecewise-linear curve simplification is also briefly surveyed.
... The most important feature of the cell structure is that it represents adjacency, or topological neighborhood information, with minimal memory requirement. The cell structure has also been designed with access methods that support a wide variety of visualization algorithms [5]. Pixel: A pixel (8) is a primary two-dimensional cell. ...
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Many branches of biomedical science and engineering require geometric modelling of human body parts. The success of magnetic resonance imaging (MRI) and other imaging modalities of computer-aided tomography has lead to many achievements in the scientific visualization of parts of the human body [1],[2]. Typical methods based on slice data generate geometries containing hundreds of thousands triangles that provide excellent details for 3D visualizations, but cannot be used directly for scientific analysis with numerical methods because of to their huge size and lack of “smoothness.”
There is nowadays an increasing need in interaction between discrete surfaces (2-manifolds) and images. More specifically, segmentation and registration of n-dimensional images are taking advantage of a priori geometrical information, most often provided as discrete 2-manifolds. Most of the publicly available libraries are oriented either toward mesh processing or image process-ing. Through a careful study we will show that none of those libraries are complete enough to fullfill image, surface and joint image-surface interaction. We propose to implement in ITK library a powerful 2-manifold data structure. The choice of ITK was driven by the fact that it provides the best base framework along with a strong n-dimensional image kernel. Based on a Quad-Edge data structure, it has been specifically tailored not only to represent orientable 2-manifolds (surfaces of real objects) but also ease further processing. We illustrate the integration of the design into ITK as a native object, enhancing existing algorithms. We also illustrate the power of the new design for further surface processing.
