The power crust is a construction which takes a sample of points from the surface of a three-dimensional object and produces a surface mesh and an approximate medial axis. The approach is to first approximate the medial axis transform (MAT) of the object. We then use an inverse transform to produce the surface representation from the MAT.This idea leads to a simple algorithm with theoretical guarantees comparable to those of other surface reconstruction and medial axis approximation algorithms. It also comes with a guarantee that does not depend in any way on the quality of the input point sample. Any input gives an output surface which is the `watertight' boundary of a three-dimensional polyhedral solid: the solid described by the approximate MAT. This unconditional guarantee makes the algorithm quite robust and eliminates the polygonalization, hole-filling or manifold extraction post-processing steps required in previous surface reconstruction algorithms.In this paper, we use the theory to develop a power crust implementation which is indeed robust for realistic and even difficult samples. We describe the careful design of a key subroutine which labels parts of the MAT as inside or outside of the object, easy in theory but non-trivial in practice. We find that we can handle areas in which the input sampling is scanty or noisy by simply discarding the unreliable parts of the MAT approximation. We demonstrate good empirical results on inputs including models with sharp corners, sparse and unevenly distributed point samples, holes, and noise, both natural and synthetic.We also demonstrate some simple extensions: intentionally leaving holes where there is no data, producing approximate offset surfaces, and simplifying the approximate MAT in a principled way to preserve stable features.

The power crust

https://u.math.biu.ac.il/~katzmik/goldman05.pdf

Curvature formulas for implicit curves and surfaces

The objective of this paper is to identify a numerical method to simulate motion of a packed or fluidized bed of fuel particles in combustion chambers, such as a grate furnace and a rotary kiln. Therefore, the various numerical methods applied in the areas of granular matter and molecular dynamics were reviewed extensively. As a result, a time driven approach was found to be suited for the numerical simulation of particle motion in combustion chambers. Furthermore, this method can also be employed to moving boundaries which are required for the present application e.g. travelling grate. The method works in a Lagrangian frame of reference, which uses the position and orientation of particles as independent variables. These are obtained by time integration of the three-dimensional dynamics equations derived from the classical Newtonian approach for each particle. This includes the keeping track of all forces and momentums acting on each particle at every time step. Viscoelastic contact forces include normal and tangential components with viscoelastic models for energy dissipation and friction. The particle shapes are approximated by spheres and ellipsoids with a varying size and ratio of the semi-axis accounting for the variety of particle geometries in a combustion chamber. For these shapes the overlap of particles during contact is expressed by a polynomial of 4th order in the two-dimensional case and a polynomial of 6th order in the three-dimensional case. A new algorithm to detect two-dimensional elliptical particle contact with sufficient accuracy was developed. It is based on a sequence of coordinate transformations and has demonstrated its reliability in numerous applications. Finally, the method was applied to simulate the motion of spherical and elliptical particles in a rectangular enclosure, on a travelling grate, and in a rotary kiln.

An approach to simulate the motion of spherical and non-spherical fuel particles in combustion chambers

Applications of of the medial axis have been limited because of its instability and algebraic complexity. In this paper, we use a simplification of the medial axis, the θ-SMA, that is parameterized by a separation angle (θ) formed by the vectors connecting a point on the medial axis to the closest points on the boundary. We present a formal characterization of the degree of simplification of the θ-SMA as a function of θ, and we quantify the degree to which the simplified medial axis retains the features of the original polyhedron.We present a fast algorithm to compute an approximation of the θ-SMA. It is based on a spatial subdivision scheme, and uses fast computation of a distance field and its gradient using graphics hardware. The complexity of the algorithm varies based on the error threshold that is used, and is a linear function of the input size. We have applied this algorithm to approximate the SMA of models with tens or hundreds of thousands of triangles. Its running time varies from a few seconds, for a model consisting of hundreds of triangles, to minutes for highly complex models.

/pdf/efficient-computation-of-a-simplified-medial-axis-3xqjv5k69o.pdf

Efficient computation of a simplified medial axis

Medial axis as a compact representation of shapes has evolved as 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 approximate them. One line of research considers the point cloud representation of the boundary surface of a solid and then attempts to compute an approximate medial axis from this point sample. It is known that the Voronoi vertices converge to the medial axis for a curve in 2D as the sample density approaches infinity. Unfortunately, the same is not true in 3D. Recently, it is discovered that a subset of Voronoi vertices called poles converge to the medial axis in 3D. However, in practice, a continuous approximation as opposed to a discrete one is sought. Recently few algorithms have been proposed which use the Voronoi diagram and its derivatives to compute this continuous approximation. These algorithms are scale or density dependent. Most of them do not have convergence guarantees, and one of them computes it indirectly from the power diagram of the poles. Recently, we proposed a new algorithm that approximates the medial axis straight from the Voronoi diagram in a scale and density independent manner with convergence guarantees. In this paper, we present several experimental results with this algorithm that support our theoretical claims and also show its effectiveness on practical data sets.

/pdf/approximate-medial-axis-as-a-voronoi-subcomplex-3wt0xx9ifl.pdf

Approximate medial axis as a Voronoi subcomplex

Shape skeletons are powerful geometric abstractions that provide useful intermediate representations for a number of geometric operations on solid models including feature recognition, shape decomposition, finite element mesh generation, and shape design As a result there has been significant interest in the development of effective methods for skeleton generation of general free-form solids In this paper we describe a method that combines Delaunay triangulation with local numerical optimization schemes for the generation of accurate skeletons of 3D implicit solid models The proposed method accelerates the slow convergence of Voronoi diagrams to the skeleton, which, without optimization, would require impraelically large sample point sets and resulting meshes to attain acceptable accuracy The Delaunay triangulation forms the basis for generating the topological structure of the skeleton The optimization step of the process generates the geometry of the skeleton patches by moving the vertices of Delaunay tetrahedra and relocating their centres to form maximally inscribed spheres The computational advantage of the optimization scheme is that it involves the solution of one small optimization problem per tetrahedron and its complexity is therefore only linear (O(n)) in the number of points used for the skeleton approximation We demonstrate the effectiveness of the method on a number of representative solid models

Munikumar S. Vimawala

Papers

An accelerated triangulation method for computing the skeletons of free-form solid models

Computational procedures for topological shape design