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26
A New VoronoiBased Surface Reconstruction Algorithm
, 2002
"... We describe our experience with a new algorithm for the reconstruction of surfaces from unorganized sample points in R³. The algorithm is the first for this problem with provable guarantees. Given a “good sample” from a smooth surface, the output is guaranteed to be topologically correct and converg ..."
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Cited by 422 (9 self)
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We describe our experience with a new algorithm for the reconstruction of surfaces from unorganized sample points in R³. The algorithm is the first for this problem with provable guarantees. Given a “good sample” from a smooth surface, the output is guaranteed to be topologically correct and convergent to the original surface as the sampling density increases. The definition of a good sample is itself interesting: the required sampling density varies locally, rigorously capturing the intuitive notion that featureless areas can be reconstructed from fewer samples. The output mesh interpolates, rather than approximates, the input points. Our algorithm is based on the threedimensional Voronoi diagram. Given a good program for this fundamental subroutine, the algorithm is quite easy to implement.
Fast surface reconstruction using the level set method
 In VLSM ’01: Proceedings of the IEEE Workshop on Variational and Level Set Methods
, 2001
"... In this paper we describe new formulations and develop fast algorithms for implicit surface reconstruction based on variational and partial differential equation (PDE) methods. In particular we use the level set method and fast sweeping and tagging methods to reconstruct surfaces from scattered data ..."
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Cited by 149 (12 self)
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In this paper we describe new formulations and develop fast algorithms for implicit surface reconstruction based on variational and partial differential equation (PDE) methods. In particular we use the level set method and fast sweeping and tagging methods to reconstruct surfaces from scattered data set. The data set might consist of points, curves and/or surface patches. A weighted minimal surfacelike model is constructed and its variational level set formulation is implemented with optimal efficiency. The reconstructed surface is smoother than piecewise linear and has a natural scaling in the regularization that allows varying flexibility according to the local sampling density. As is usual with the level set method we can handle complicated topology and deformations, as well as noisy or highly nonuniform data sets easily. The method is based on a simple rectangular grid, although adaptive and triangular grids are also possible. Some consequences, such as hole filling capability, are demonstrated, as well as the viability and convergence of our new fast tagging algorithm.
A Simple Provable Algorithm for Curve Reconstruction
, 1998
"... We present an algorithm that provably reconstructs a curve in the framework introduced by Amenta, Bern and Eppstein. The highlights of the algorithm are: (i) it is simple, (ii) it requires a sampling density better than previously known, (iii) it can be adapted for curve reconstruction in higher dim ..."
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Cited by 54 (12 self)
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We present an algorithm that provably reconstructs a curve in the framework introduced by Amenta, Bern and Eppstein. The highlights of the algorithm are: (i) it is simple, (ii) it requires a sampling density better than previously known, (iii) it can be adapted for curve reconstruction in higher dimensions straightforwardly.
Approximating the Medial Axis from the Voronoi Diagram with a Convergence Guarantee
 Algorithmica
, 2004
"... The medial axis of a surface in 3D is the closure of all points that have two or more closest points on the surface. It is an essential geometric structure in a number of applications involving 3D geometric shapes. Since exact computation of the medial axis is difficult in general, efforts continue ..."
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Cited by 46 (8 self)
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The medial axis of a surface in 3D is the closure of all points that have two or more closest points on the surface. It is an essential geometric structure in a number of applications involving 3D geometric shapes. Since exact computation of the medial axis is difficult in general, efforts continue to improve their approximations. Voronoi diagrams turn out to be useful for this approximation. Although it is known that Voronoi vertices for a sample of points from a curve in 2D approximate its medial axis, similar result does not hold in 3D. Recently, it has been discovered that only a subset of Voronoi vertices converge to the medial axis as sample density approaches infinity. However, most applications need a nondiscrete approximation as opposed to a discrete one. To date no known algorithm can compute this approximation straight from the Voronoi diagram with a guarantee of convergence. We present such an algorithm and its convergence analysis in this paper. One salient feature of the algorithm is that it is scale and density independent. Experimental results corroborate our theoretical claims.
New Techniques for Topologically Correct Surface Reconstruction
, 2000
"... We present a new approach to surface reconstruction based on the Delaunay complex. First we give a simple and fast algorithm that picks locally a surface at each vertex. For that, we introduce the concept of lambdaintervals. It turns out that for smooth regions of the surface this method works very ..."
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Cited by 35 (4 self)
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We present a new approach to surface reconstruction based on the Delaunay complex. First we give a simple and fast algorithm that picks locally a surface at each vertex. For that, we introduce the concept of lambdaintervals. It turns out that for smooth regions of the surface this method works very well and at difficult parts of the surface yields an output wellsuited for postprocessing. As a postprocessing step we propose a topological clean up and a new technique based on linear programming in order to establish a topologically correct surface. These techniques should be useful also for many other reconstruction schemes.
Shape dimension and approximation from samples
 Symposium on Discrete Algorithms (SODA
, 2002
"... There are many scientific and engineering applications where an automatic detection of shape dimension from sample data is necessary. Topological dimensions of shapes constitute an important global feature of them. We present a Voronoi based dimension detection algorithm that assigns a dimension t ..."
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Cited by 31 (7 self)
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There are many scientific and engineering applications where an automatic detection of shape dimension from sample data is necessary. Topological dimensions of shapes constitute an important global feature of them. We present a Voronoi based dimension detection algorithm that assigns a dimension to a sample point which is the topological dimension of the manifold it belongs to. Based on this dimension detection, we also present an algorithm to approximate shapes of arbitrary dimension from their samples. Our empirical results with data sets in three dimensions support our theory. 1 Introduction. Interpretation of shapes from its samples is needed in many scientific and engineering applications. As a result, defining
Regular and NonRegular Point Sets: Properties and Reconstruction
 IN "COMPUTATIONAL GEOMETRY  THEORY AND APPLICATION"
"... In this paper, we address the problem of curve and surface reconstruction from sets of points. We introduce regular interpolants, which are polygonal approximations of curves and surfaces satisfying a new regularity condition. This new condition, which is an extension of the popular notion ofsampli ..."
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Cited by 22 (0 self)
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In this paper, we address the problem of curve and surface reconstruction from sets of points. We introduce regular interpolants, which are polygonal approximations of curves and surfaces satisfying a new regularity condition. This new condition, which is an extension of the popular notion ofsampling to the practical case of discrete shapes, seems much more realistic than previously proposed conditions based on properties of the underlying continuous shapes. Indeed, contrary to previous sampling criteria, our regularity condition can be checked on the basis of the samples alone and can be turned into a provably correct curve and surface reconstruction algorithm. Our reconstruction methods can also be applied to nonregular and unorganized point sets, revealing a larger part of the inner structure of such point sets than past approaches. Several realsize reconstruction examples validate the new method.
Reconstructing a Collection of Curves with Corners and Endpoints
 Proc. 12th Annu. ACMSIAM Sympos. Discrete Alg
, 2001
"... We present an algorithm which provably reconstructs a collection of curves with corners and endpoints from a sample set that satisfies a certain sampling condition. The algorithm outputs a polygonal reconstruction that contains the edges in the correct reconstruction of the curves and such that any ..."
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Cited by 13 (4 self)
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We present an algorithm which provably reconstructs a collection of curves with corners and endpoints from a sample set that satisfies a certain sampling condition. The algorithm outputs a polygonal reconstruction that contains the edges in the correct reconstruction of the curves and such that any additional edge between sample points is justified. Furthermore, we show that for any such collection of curves, there exists a sample set such that a slightly modified version of our algorithm outputs exactly the correct reconstruction. The algorithm also performs quite well in practice. 1
Visual hull construction using adaptive sampling
 IEEE Workshops Appl. Comput. Vision
, 2005
"... Volumetric visual hulls have become very popular in many computer vision applications including human body pose estimation and virtualized reality. In these applications, the visual hull is used to approximate the 3D geometry of an object. Existing volumetric visual hull construction techniques, ..."
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Cited by 13 (0 self)
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Volumetric visual hulls have become very popular in many computer vision applications including human body pose estimation and virtualized reality. In these applications, the visual hull is used to approximate the 3D geometry of an object. Existing volumetric visual hull construction techniques, however, produce a 3color volume data that merely serves as a bounding volume. In other words it lacks an accurate surface representation. Polygonization can produce satisfactory results only at high resolutions. In this study we extend the binary visual hull to an implicit surface in order to capture the geometry of the visual hull itself. In particular, we introduce an octreebased visual hull specific adaptive sampling algorithm to obtain a volumetric representation that provides accuracy proportional to the level of detail. Moreover, we propose a method to process the resulting octree to extract a crackfree polygonal visual hull surface. Experimental results illustrate the performance of the algorithm. 1.