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254
Smooth Surface Reconstruction from Noisy Clouds
"... We describe a new method for surface reconstruction and smoothing based on unorganized noisy point clouds without normals. The output of the method is a refined triangular mesh that approximates the original point cloud while preserving the fine details present in the underlying surface. The method ..."
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Cited by 4 (0 self)
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We describe a new method for surface reconstruction and smoothing based on unorganized noisy point clouds without normals. The output of the method is a refined triangular mesh that approximates the original point cloud while preserving the fine details present in the underlying surface. The method
A fast and robust algorithm to count topologically persistent holes in noisy clouds
"... Preprocessing a 2D image often produces a noisy cloud of interest points. We study the problem of counting holes in noisy clouds in the plane. The holes in a given cloud are quantified by the topological persistence of their boundary contours when the cloud is analyzed at all possible scales. We des ..."
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Preprocessing a 2D image often produces a noisy cloud of interest points. We study the problem of counting holes in noisy clouds in the plane. The holes in a given cloud are quantified by the topological persistence of their boundary contours when the cloud is analyzed at all possible scales. We
Reconstruction and Representation of 3D Objects with Radial Basis Functions
 Computer Graphics (SIGGRAPH ’01 Conf. Proc.), pages 67–76. ACM SIGGRAPH
, 2001
"... We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from pointcloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs al ..."
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Cited by 505 (1 self)
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We use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from pointcloud data and to repair incomplete meshes. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. Fast methods for fitting and evaluating RBFs
Spectral Surface Reconstruction from Noisy Point Clouds
, 2004
"... We introduce a noiseresistant algorithm for reconstructing a watertight surface from point cloud data. It forms a
..."
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Cited by 81 (1 self)
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We introduce a noiseresistant algorithm for reconstructing a watertight surface from point cloud data. It forms a
Robust smoothing of noisy point clouds
 PROC. SIAM CONFERENCE ON GEOMETRIC DESIGN AND COMPUTING
, 2003
"... This paper addresses the problem of removing the noise from noisy points clouds in the context of surface reconstruction. We introduce a new smoothing operator Q inspired by the moving leastsquares method and robust statistics theory. Our method can be seen as an improvement of the moving leastsqu ..."
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Cited by 6 (1 self)
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This paper addresses the problem of removing the noise from noisy points clouds in the context of surface reconstruction. We introduce a new smoothing operator Q inspired by the moving leastsquares method and robust statistics theory. Our method can be seen as an improvement of the moving least
Visibility of Noisy Point Cloud Data
 IEEE INTERNATIONAL CONFERENCE ON SHAPE MODELING AND APPLICATIONS (SMI) 2010
, 2010
"... We present a robust algorithm for estimating visibility from a given viewpoint for a point set containing concavities, nonuniformly spaced samples, and possibly corrupted with noise. Instead of performing an explicit surface reconstruction for the points set, visibility is computed based on a const ..."
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Cited by 9 (0 self)
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We present a robust algorithm for estimating visibility from a given viewpoint for a point set containing concavities, nonuniformly spaced samples, and possibly corrupted with noise. Instead of performing an explicit surface reconstruction for the points set, visibility is computed based on a construction involving convex hull in a dual space, an idea inspired by the work of Katz et al. [26]. We derive theoretical bounds on the behavior of the method in the presence of noise and concavities, and use the derivations to develop a robust visibility estimation algorithm. In addition, computing visibility from a set of adaptively placed viewpoints allows us to generate locally consistent partial reconstructions. Using a graph based approximation algorithm we couple such reconstructions to extract globally consistent reconstructions. We test our method on a variety of 2D and 3D point sets of varying complexity and noise content.
Normal and Feature Approximations from Noisy Point Clouds
"... We consider the problem of approximating normal and feature sizes of a surface from point cloud data that may be noisy. These problems are central to many applications dealing with point cloud data. In the noisefree case, the normals and feature sizes can be approximated by the centers of a set of ..."
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Cited by 12 (0 self)
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We consider the problem of approximating normal and feature sizes of a surface from point cloud data that may be noisy. These problems are central to many applications dealing with point cloud data. In the noisefree case, the normals and feature sizes can be approximated by the centers of a set
Surface Reconstruction from Noisy Point Clouds
, 2005
"... We show that a simple modification of the power crust algorithm for surface reconstruction produces correct outputs in presence of noise. This is proved using a fairly realistic noise model. Our theoretical results are related to the problem of computing a stable subset of the medial axis. We demost ..."
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Cited by 15 (0 self)
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We show that a simple modification of the power crust algorithm for surface reconstruction produces correct outputs in presence of noise. This is proved using a fairly realistic noise model. Our theoretical results are related to the problem of computing a stable subset of the medial axis. We demostrate the effectiveness of our algorithm with a number of experimental results.
Extracting lines of curvature from noisy point clouds
"... We present a robust framework for extracting lines of curvature from point clouds. First, we show a novel approach to denoising the input point cloud using robust statistical estimates of surface normal and curvature which automatically rejects outliers and corrects points by energy minimization. Th ..."
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Cited by 8 (1 self)
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the lines of curvature for featurepreserving mesh construction directly from noisy point clouds. Key words: lines of curvature, robust curvature estimation, point cloud denoising, outlier rejection, quad mesh construction 1
Scale Selection for Geometric Fitting in Noisy Point Clouds
 INTERNATIONAL JOURNAL OF COMPUTATIONAL GEOMETRY & APPLICATIONS
, 2010
"... In recent years, there has been a resurgence in the use of raw point cloud data as the geometric primitive of choice for several modeling tasks such as rendering, editing and compression. Algorithms using this representation often require reliable additional information such as the curve tangent o ..."
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Cited by 2 (0 self)
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In recent years, there has been a resurgence in the use of raw point cloud data as the geometric primitive of choice for several modeling tasks such as rendering, editing and compression. Algorithms using this representation often require reliable additional information such as the curve tangent
Results 1  10
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254