An automatic edge-collapse based simplification method has been proposed for decimation of polygonal models and generating their LODs (Levels of detail). The measure of geometric fidelity employed is motivated by the normal space deviation of a polygonal model arising during its decimation process and forces the algorithm to minimize the normal space deviation. In spite of the global nature of the evaluation of geometric deviation, the algorithm is memory efficient and involves less execution time then the state-of-the art simplification algorithms. This automatically prevents the creation of folds and automatically preserves visually important features of the model even at low levels of detail. LODs generated by our method compare favorably with those produced by the standard QEM-based algorithm QSlim in terms of the mean and maximum geometric errors, whereas its performance in preserving normal space of the original model is better than that of QSlim.
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Triangular meshes are widely used in computer graphics fields, such as GIS, CAD and VR. Very complex models, with hundreds of thousands of faces, are easily produced by curremt CAD tools, automatic acquisition devices, or by fitting isosurfaces out of volume datasets. Many geometric datasets require a larg amount of disk space. One of the solutions is to compress those large geometric data sets with geometric compression algorithms. On the other hand, a highly complex data representation is not always necessery. For example, a full size model is not required for generation of each frame of an interactive visualization. This has led to substantial research on the surface mesh compression or mesh simplification. We present a method to deal with both issues. It breaks down the triangle meshes into a set of triangle strips and vertex chains. Following that, inter-triangle-strip simplification and intra-triangle-strip simplification are used to simplify the meshes. The method can not only compress the mesh geometry datasets for hard disk storage, but also simplify the meshes for the purposes of rendering and displaying. The results show the validity and efficiency of our method.
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This paper presents algorithms to implement the estimation of motion, focusing on the finite element method as a framework for the development of techniques. The finite element approach has the advantages of a rigorous mathematical formulation, speed of reconstruction, conceptual simplicity and ease of implementation via well-established finite element procedures in comparison to finite volume or finite difference techniques. The finite elemcnt techniques are implemented using a triangular discretisation, and preliminary results are presented. An important advantage is the capacity to tackle problems in which non-uniform sampling of the image sequence is appropriate.
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