Recently developed 3D scanning devices are capable of capturing point clouds, as well as additional information, such as normals and texture. This paper describes a new and fast reverse engineering method for creating...
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Recently developed 3D scanning devices are capable of capturing point clouds, as well as additional information, such as normals and texture. This paper describes a new and fast reverse engineering method for creating a 3D computerized model from data captured by such contemporary 3D scanning devices. The proposed method aggregates large-scale 3D scanned data into an extended Hierarchical Space Decomposition Model (HSDM) based on Octree data structure. This model can represent both an object’s boundary surface and its interior volume. The HSDM enables data reduction, while preserving sharp geometrical features and object topology. As a result the execution time of the reconstruction process is significantly reduced. Moreover, the proposed model naturally allows multiresolution surface reconstruction, represented by a mesh with regular properties. Based on the proposed volumetric model, the surface reconstruction process becomes more robust and stable with respect to sampling noise.
Given a connected, weighted, undirected graph G and a bound D, the bounded-diameter minimum spanning tree problem seeks a spanning tree on G of lowest weight in which no path between two vertices contains more than D ...
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ISBN:
(纸本)9781581136241
Given a connected, weighted, undirected graph G and a bound D, the bounded-diameter minimum spanning tree problem seeks a spanning tree on G of lowest weight in which no path between two vertices contains more than D edges. This problem is NP-hard for 4 ≤ D
Partitioning is a fundamental operation on graphs. In this paper we briefly review the basic concepts of graph partitioning and its relationship to digital mesh processing. We also elaborate on the connection between ...
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Partitioning is a fundamental operation on graphs. In this paper we briefly review the basic concepts of graph partitioning and its relationship to digital mesh processing. We also elaborate on the connection between graph partitioning and spectral graph theory. Applications in computergraphics are described.
We present a distributed scene graph architecture for use in the blue-c, a novel collaborative immersive virtual environment. We extend the widely used OpenGL Performer toolkit to provide a distributed scene graph mai...
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We present a distributed scene graph architecture for use in the blue-c, a novel collaborative immersive virtual environment. We extend the widely used OpenGL Performer toolkit to provide a distributed scene graph maintaining full synchronization down to vertex and texel level. We propose a synchronization scheme including customizable, relaxed locking mechanisms. We demonstrate the functionality of our toolkit with two prototype applications in our high-performance virtual reality and visual simulation environment.
We describe an innovative system designed for museums to create, manage and present multimedia based representations of museum artefacts in virtual exhibitions both inside and outside museums. Our system creates digit...
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We present a robust image synthesis method to automatically infer missing information from a damaged 2D image by tensor voting. Our method translates image color and texture information into an adaptive ND tensor, fol...
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ISBN:
(纸本)0769519008
We present a robust image synthesis method to automatically infer missing information from a damaged 2D image by tensor voting. Our method translates image color and texture information into an adaptive ND tensor, followed by a voting process that infers non-iteratively the optimal color values in the ND texture space for each defective pixel. ND tensor voting can be applied to images consisting of roughly homogeneous and periodic textures (e.g. a brick wall), as well as difficult images of natural scenes, which contain complex color and texture information. To effectively tackle the latter type of difficult images, a two-step method is proposed. First, we perform texture-based segmentation in the input image, and extrapolate partitioning curves to generate a complete segmentation for the image. Then, missing colors are synthesized using ND tensor voting. Automatic tensor scale analysis is used to adapt to different feature scales inherent in the input. We demonstrate the effectiveness of our approach using a difficult set of real images.
A "graphics for vision" approach is proposed to address the problem of reconstruction from a large and imperfect data set: reconstruction on demand by tensor voting, or ROD-TV. ROD-TV simultaneously delivers...
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ISBN:
(纸本)0769519008
A "graphics for vision" approach is proposed to address the problem of reconstruction from a large and imperfect data set: reconstruction on demand by tensor voting, or ROD-TV. ROD-TV simultaneously delivers good efficiency and robustness, by adapting to a continuum of primitive connectivity, view dependence, and levels of detail (LOD). Locally inferred surface elements are robust to noise and better capture local shapes. By inferring per-vertex normals at sub-voxel precision on the fly, we can achieve interpolative shading. Since these missing details can be recovered at the current level of detail, our result is not upper bounded by the scanning resolution. By relaxing the mesh connectivity requirement, we extend ROD-TV and propose a simple but effective multiscale feature extraction algorithm. ROD-TV consists of a hierarchical data structure that encodes different levels of detail. The local reconstruction algorithm is tensor voting. It is applied on demand to the visible subset of data at a desired level of detail, by traversing the data hierarchy and collecting tensorial support in a neighborhood. We compare our approach and present encouraging results.
Estimating intrinsic geometric properties of a surface from a polygonal mesh obtained from range data is an important stage of numerous algorithms in computer and robot vision, computergraphics, geometric modeling, i...
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Estimating intrinsic geometric properties of a surface from a polygonal mesh obtained from range data is an important stage of numerous algorithms in computer and robot vision, computergraphics, geometric modeling, industrial and biomedical engineering. This work considers different computational schemes for local estimation of intrinsic curvature geometric properties. Five different algorithms and their modifications were tested on triangular meshes that represent tessellations of synthetic geometric models. The results were compared with the analytically computed values of the Gaussian and mean curvatures of the non-uniform rational B-spline (NURBs) surfaces, these meshes originated from. This work manifests the best algorithms suited for that indeed different algorithms should be employed to compute the Gaussian and mean curvatures.
Despite extensive research and rapid increase of computing power, free-form object matching still remains a challenging problem in CAD/CAM areas. In this paper, various object features are discussed, and matching meth...
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Despite extensive research and rapid increase of computing power, free-form object matching still remains a challenging problem in CAD/CAM areas. In this paper, various object features are discussed, and matching methods which use these features are introduced along with robust computational algorithms for umbilical points and intrinsic wireframes. The similarity of matched objects is assessed with three proposed tests. Each algorithm is demonstrated with examples.
We consider the problem of representing size information in the edges and vertices of a planar graph. Such information can be used, for example, to depict a network of computers and information traveling through the n...
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