A New Strategy for Scattered Data Approximation Using Radial Basis Functions Respecting Points of Inflection

Cervenka, Martin; Smolik, Michal; Skala, Václav

doi:10.1007/978-3-030-24289-3_24

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Geometrical Static Model1

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2019

2024

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Cited by 5 publications

(1 citation statement)

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“…The findings indicated that the Halton distribution emerged as the most effective option, which is following other research (see, e.g. [43], [49]).…”

Section: Geometrical Static Modelsupporting

confidence: 84%

A novel radial basis function description of a smooth implicit surface for musculoskeletal modelling

Cervenka,

Kohout,

Lipus

2024

Preprint

Self Cite

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As musculoskeletal illnesses continue to increase, useful computerised muscle modelling is crucial. This paper addresses this concern by proposing a mathematical model for a dynamic 3D geometrical surface representation of muscles using a Radial Basis Function (RBF) approximation technique. The objective is to obtain a smoother surface while minimising data use, contrasting it from classical polygonal (e.g., triangular) surface mesh models or volumetric (e.g., tetrahedral) mesh models. The novel method is tested on multiple data sets, and the experiments show good results according to the introduced metrics.

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“…The findings indicated that the Halton distribution emerged as the most effective option, which is following other research (see, e.g. [43], [49]).…”

Section: Geometrical Static Modelsupporting

confidence: 84%