Results 71 to 80 of about 2,931,499 (197)

Measure characterizations and properties of normal and regular lattices

open access: yesInternational Journal of Mathematics and Mathematical Sciences, 1991
Various equivalent characterizations of normality are considered and a measure theoretic definition is given for strongly normal lattices. Measure conditions related to the apace of σ-smooth, lattice-regular, 0−1 measures are noted which imply, or are ...
Peter M. Grassi
doaj   +1 more source

Survey on differential estimators for 3d point clouds

open access: yesComputer 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   +4 more
wiley   +1 more source

Exact Hausdorff Measures of Cantor Sets

open access: yes, 2014
Cantor sets in R are common examples of sets for which Hausdorff measures can be positive and fnite. However, there exist Cantor sets for which no Hausdorff measure is supported and finite.
Pal\uf6 Forsstr\uf6m, Malin   +2 more
core   +1 more source

Establishing Shape Correspondences: A Survey

open access: yesComputer 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

On comparable and non-comparable Hausdorff measures [PDF]

open access: yes, 2014
Розвиток загальних методiв обчислення розмiрностi Хаусдорфа–Безиковича — одна з центральних проблем теорiї фракталiв. Дослiджено тривiальнiсть (нетривiальнiсть) мережевих мiр Хаусдорфа.
Торбін, Г.М.   +1 more
core   +2 more sources

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

open access: yesComputer 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

A Decision-Making Method for Lung Diseases Recognition Using Generalized Complex Fermatean Fuzzy Distance and Entropy Measures

open access: yesInternational Journal of Computational Intelligence Systems
Complex Fermatean fuzzy sets (CFFSs) represent an advanced development of fuzzy sets by integrating aspects of complex fuzzy sets and Fermatean fuzzy sets.
Zhe Liu   +4 more
doaj   +1 more source

Medial Axis Aware Learning of Signed Distance Functions

open access: yesComputer 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   +2 more
wiley   +1 more source

Progressive Convex Hull Simplification

open access: yesComputer 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

A practical algorithm for weighted k‐hulls

open access: yesComputer 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

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