Results 1  10
of
25
A Survey of PointBased Techniques in Computer Graphics
 Computers & Graphics
, 2004
"... In recent years pointbased geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of highly complex 3Dmodels. Point sampled objects do neither have to store nor to maintain globally consistent topological ..."
Abstract

Cited by 84 (4 self)
 Add to MetaCart
In recent years pointbased geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of highly complex 3Dmodels. Point sampled objects do neither have to store nor to maintain globally consistent topological information. Therefore they are more flexible compared to triangle meshes when it comes to handling highly complex or dynamically changing shapes. In this paper, we make an attempt to give an overview of the various pointbased methods that have been proposed over the last years. In particular we review and evaluate different shape representations, geometric algorithms, and rendering methods which use points as a universal graphics primitive.
Algebraic point set surfaces
 IN PROCEEDINGS SIGGRAPH ’07
, 2007
"... In this paper we present a new Point Set Surface (PSS) definition based on moving least squares (MLS) fitting of algebraic spheres. Our surface representation can be expressed by either a projection procedure or in implicit form. The central advantages of our approach compared to existing planar M ..."
Abstract

Cited by 80 (8 self)
 Add to MetaCart
In this paper we present a new Point Set Surface (PSS) definition based on moving least squares (MLS) fitting of algebraic spheres. Our surface representation can be expressed by either a projection procedure or in implicit form. The central advantages of our approach compared to existing planar MLS include significantly improved stability of the projection under low sampling rates and in the presence of high curvature. The method can approximate or interpolate the input point set and naturally handles planar point clouds. In addition, our approach provides a reliable estimate of the mean curvature of the surface at no additional cost and allows for the robust handling of sharp features and boundaries. It processes a simple point set as input, but can also take significant advantage of surface normals to improve robustness, quality and performance. We also present an novel normal estimation procedure which exploits the properties of the spherical fit for both direction estimation and orientation propagation. Very efficient computational procedures enable us to compute the algebraic sphere fitting with up to 40 million points per second on latest generation GPUs.
On normals and projection operators for surfaces defined by point sets
 IN EUROGRAPHICS SYMP. ON POINTBASED GRAPHICS
, 2004
"... Levin’s MLS projection operator allows defining a surface from a set of points and represents a versatile procedure to generate points on this surface. Practical problems of MLS surfaces are a complicated nonlinear optimization to compute a tangent frame and the (commonly overlooked) fact that the ..."
Abstract

Cited by 60 (3 self)
 Add to MetaCart
Levin’s MLS projection operator allows defining a surface from a set of points and represents a versatile procedure to generate points on this surface. Practical problems of MLS surfaces are a complicated nonlinear optimization to compute a tangent frame and the (commonly overlooked) fact that the normal to this tangent frame is not the surface normal. An alternative definition of Point Set Surfaces, inspired by the MLS projection, is the implicit surface version of Adamson & Alexa. We use this surface definition to show how to compute exact surface normals and present simple, efficient projection operators. The exact normal computation also allows computing orthogonal projections.
Fitting Subdivision Surfaces to Unorganized Point Data Using SDM
, 2004
"... We study the reconstruction of smooth surfaces from point clouds. We use a new squared distance error term in optimization to fit a subdivision surface to a set of unorganized points, which defines a closed target surface of arbitrary topology. The resulting method is based on the framework of squar ..."
Abstract

Cited by 21 (5 self)
 Add to MetaCart
(Show Context)
We study the reconstruction of smooth surfaces from point clouds. We use a new squared distance error term in optimization to fit a subdivision surface to a set of unorganized points, which defines a closed target surface of arbitrary topology. The resulting method is based on the framework of squared distance minimization (SDM) proposed by Pottmann et al. Specifically, with an initial subdivision surface having a coarse control mesh as input, we adjust the control points by optimizing an objective function through iterative minimization of a quadratic approximant of the squared distance function of the target shape. Our experiments show that the new method (SDM) converges much faster than the commonly used optimization method using the point distance error function, which is known to have only linear convergence. This observation is further supported by our recent result that SDM can be derived from the Newton method with necessary modifications to make the Hessian positive definite and the fact that the Newton method has quadratic convergence.
Anisotropic point set surfaces
 In Afrigaph ’06: Proceedings of the 4th international conference on Computer graphics, virtual reality, visualisation and interaction in Africa
, 2006
"... ..."
Point Cloud Collision Detection
, 2004
"... In the past few years, many efficient rendering and surface reconstruction algorithms for point clouds have been developed. ..."
Abstract

Cited by 14 (1 self)
 Add to MetaCart
In the past few years, many efficient rendering and surface reconstruction algorithms for point clouds have been developed.
PointSampled Cell Complexes
"... A piecewise smooth surface, possibly with boundaries, sharp edges, corners, or other features is defined by a set of samples. The basic idea is to model surface patches, curve segments and points explicitly, and then to glue them together based on explicit connectivity information. The geometry is d ..."
Abstract

Cited by 14 (1 self)
 Add to MetaCart
A piecewise smooth surface, possibly with boundaries, sharp edges, corners, or other features is defined by a set of samples. The basic idea is to model surface patches, curve segments and points explicitly, and then to glue them together based on explicit connectivity information. The geometry is defined as the set of stationary points of a projection operator, which is generalized to allow modeling curves with samples, and extended to account for the connectivity information. Additional tangent constraints can be used to model shapes with continuous tangents across edges and corners.
Reconstructing Manifold and NonManifold Surfaces from Point Clouds
 IN PROC. IEEE VISUALIZATION
, 2005
"... This paper presents a novel approach for surface reconstruction from point clouds. The proposed technique is general in the sense that it naturally handles both manifold and nonmanifold surfaces, providing a consistent way for reconstructing closed surfaces as well as surfaces with boundaries. It i ..."
Abstract

Cited by 12 (1 self)
 Add to MetaCart
This paper presents a novel approach for surface reconstruction from point clouds. The proposed technique is general in the sense that it naturally handles both manifold and nonmanifold surfaces, providing a consistent way for reconstructing closed surfaces as well as surfaces with boundaries. It is also robust in the presence of noise, irregular sampling and surface gaps. Furthermore, it is fast, parallelizable and easy to implement because it is based on simple local operations. In this approach, surface reconstruction consists of three major steps: first, the space containing the point cloud is subdivided, creating a voxel representation. Then, a voxel surface is computed using gap filling and topological thinning operations. Finally, the resulting voxel surface is converted into a polygonal mesh. We demonstrate the effectiveness of our approach by reconstructing polygonal models from range scans of real objects as well as from synthetic data.
Point Cloud Surfaces using Geometric Proximity Graphs
, 2004
"... We present a new definition of an implicit surface over a noisy point cloud, based on the weighted least squares approach. It can be evaluated very fast, but artifacts are significantly reduced. We propose to use a different... ..."
Abstract

Cited by 10 (0 self)
 Add to MetaCart
We present a new definition of an implicit surface over a noisy point cloud, based on the weighted least squares approach. It can be evaluated very fast, but artifacts are significantly reduced. We propose to use a different...
A Survey of Methods for Moving Least Squares Surfaces
, 2008
"... Moving least squares (MLS) surfaces representation directly defines smooth surfaces from point cloud data, on which the differential geometric properties of point set can be conveniently estimated. Nowadays, the MLS surfaces have been widely applied in the processing and rendering of pointsampled m ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
Moving least squares (MLS) surfaces representation directly defines smooth surfaces from point cloud data, on which the differential geometric properties of point set can be conveniently estimated. Nowadays, the MLS surfaces have been widely applied in the processing and rendering of pointsampled models and increasingly adopted as the standard definition of point set surfaces. We classify the MLS surface algorithms into two types: projection MLS surfaces and implicit MLS surfaces, according to employing a stationary projection or a scalar field in their definitions. Then, the properties and constrains of the MLS surfaces are analyzed. After presenting its applications, we summarize the MLS surfaces definitions in a generic form and give the outlook of the future work at last.