Results 71 to 80 of about 3,294 (223)

Survey on differential estimators for 3d point clouds

Computer Graphics Forum, EarlyView.
Abstract Recent advancements in 3D scanning technologies, including LiDAR and photogrammetry, have enabled the precise digital replication of real‐world objects. These methods are widely used in fields such as GIS, robotics, and cultural heritage. However, the point clouds generated by such scans are often noisy and unstructured, posing challenges for ...
Léo Arnal–Anger, Thibault Lejemble, David Coeurjolly, Loïc Barthe, Nicolas Mellado   +4 more
wiley   +1 more source

Establishing Shape Correspondences: A Survey

Computer Graphics Forum, EarlyView.
Abstract Shape correspondence between surfaces in 3D is a central problem in geometry processing, concerned with establishing meaningful relations between surfaces. While all correspondence problems share this goal, specific formulations can differ significantly: Downstream applications require certain properties that correspondences must satisfy ...
A. Heuschling, H. Meinhold, L. Kobbelt
wiley   +1 more source

Singular dimension of spaces of real functions

Le Matematiche, 2007
Let X be a space of measurable real functions defined on a fixed open set Ω ⊆ R^N . It is natural to define the singular dimension of X as the supremum of Hausdorff dimension of singular sets of all functions in X.We say that f ∈ X is a maximally ...
Darko Žubrinić
doaj  

A Simple Grid‐Maps Pipeline: Restructured, Accelerated and Upgraded

Computer Graphics Forum, EarlyView.
Abstract Grid maps – spatially arranged small multiples – are a powerful tool to show complex geospatial data. Meulemans et al. (2020) introduced a pipeline for computing high‐quality grid maps that are shaped roughly according to their containing geographic outlines.
W. Meulemans
wiley   +1 more source

Hausdorff dimension of fermions on a random lattice

Nuclear Physics B
Geometric properties of lattice quantum gravity in two dimensions are studied numerically via Monte Carlo on Euclidean Dynamical Triangulations. A new computational method is proposed to simulate gravity coupled with fermions, which allows the study of ...
Mattia Varrone, William E.V. Barker
doaj   +1 more source

A Hausdorff dimension for finite sets

CoRR, 2015
The classical Hausdorff dimension of finite or countable sets is zero. We define an analog for finite sets, called finite Hausdorff dimension which is non-trivial. It turns out that a finite bound for the finite Hausdorff dimension guarantees that every point of the set has "nearby" neighbors.
openaire   +2 more sources

Medial Axis Aware Learning of Signed Distance Functions

Computer Graphics Forum, EarlyView.
Abstract We propose a novel variational method to compute a highly accurate global signed distance function (SDF) to a given point cloud. To this end, the jump set of the gradient of the SDF, which coincides with the medial axis of the surface, is explicitly taken into account through a higher‐order variational formulation that enforces linear growth ...
Samuel Weidemaier, Christoph Norden‐Smoch, Martin Rumpf   +2 more
wiley   +1 more source

Progressive Convex Hull Simplification

Computer Graphics Forum, EarlyView.
Abstract Convex hulls are useful as tight bounding proxies for a variety of tasks including collision detection, ray intersection, and distance computation. Unfortunately, the complexity of polyhedral convex hulls grows linearly with their input. We consider the problem of conservatively simplifying a convex hull to a specified number of half‐spaces ...
Alec Jacobson
wiley   +1 more source

Generalized Dimensions of Self-Affine Sets with Overlaps

Fractal and Fractional
Two decades ago, Ngai and Wang introduced a well-known finite type condition (FTC) on the self-similar iterated function system (IFS) with overlaps and used it to calculate the Hausdorff dimension of self-similar sets. In this paper, inspired by Ngai and
Guanzhong Ma, Jun Luo, Xiao Zhou
doaj   +1 more source

A practical algorithm for weighted k‐hulls

Computer Graphics Forum, EarlyView.
Abstract The convex hull is a central concept in computational geometry, geometry processing, and generally for summarizing sampled data. Its descriptive power suffers significantly in the presence of noise. The k‐hull, also known as the k‐depth contour in statistics, is the intersection of all half‐spaces that contain all but k data points, i.e. it is
N. Look, H. Meyer, M. Alexa
wiley   +1 more source