Matches in SemOpenAlex for { <https://semopenalex.org/work/W2022854974> ?p ?o ?g. }
- W2022854974 endingPage "430" @default.
- W2022854974 startingPage "417" @default.
- W2022854974 abstract "Reverse Engineering (RE) requires representing with free forms (NURBS, Spline, Bézier) a real surface $$S_0$$ which has been point-sampled. To serve this purpose, we have implemented an algorithm that minimizes the accumulated distance between the free form and the (noisy) point sample. We use a dual-distance calculation point to / from surfaces, which discourages the forming of outliers and artifacts. This algorithm seeks a minimum in a function $$f$$ that represents the fitting error, by using as tuning variable the control polyhedron for the free form. The topology (rows, columns) and geometry of the control polyhedron are determined by alternative geodesic-based dimensionality reduction methods: (a) graph-approximated geodesics (Isomap), or (b) PL orthogonal geodesic grids. We assume the existence of a triangular mesh of the point sample (a reasonable expectation in current RE). A bijective composition mapping $$S_0 subset mathbb {R}^3 longleftrightarrow mathbb {R}^2$$ allows to estimate a size of the control polyhedrons favorable to uniform-speed parameterizations. Our results show that orthogonal geodesic grids is a direct and intuitive parameterization method, which requires more exploration for irregular triangle meshes. Isomap gives a usable initial parameterization whenever the graph approximation of geodesics on $$S_0$$ be faithful. These initial guesses, in turn, produce efficient free form optimization processes with minimal errors. Future work is required in further exploiting the usual triangular mesh underlying the point sample for (a) enhancing the segmentation of the point set into faces, and (b) using a more accurate approximation of the geodesic distances within $$S_0$$ , which would benefit its dimensionality reduction." @default.
- W2022854974 created "2016-06-24" @default.
- W2022854974 creator A5007985159 @default.
- W2022854974 creator A5016267951 @default.
- W2022854974 creator A5016771293 @default.
- W2022854974 creator A5026669578 @default.
- W2022854974 creator A5065987514 @default.
- W2022854974 creator A5069420524 @default.
- W2022854974 date "2014-10-19" @default.
- W2022854974 modified "2023-10-10" @default.
- W2022854974 title "Geodesic-based manifold learning for parameterization of triangular meshes" @default.
- W2022854974 cites W1965522022 @default.
- W2022854974 cites W1969014399 @default.
- W2022854974 cites W1973509684 @default.
- W2022854974 cites W1973947322 @default.
- W2022854974 cites W1994581678 @default.
- W2022854974 cites W1995225493 @default.
- W2022854974 cites W2001141328 @default.
- W2022854974 cites W2016848393 @default.
- W2022854974 cites W2023808821 @default.
- W2022854974 cites W2030387606 @default.
- W2022854974 cites W2044084800 @default.
- W2022854974 cites W2052286413 @default.
- W2022854974 cites W2064058834 @default.
- W2022854974 cites W2072814083 @default.
- W2022854974 cites W2078095246 @default.
- W2022854974 cites W2087070363 @default.
- W2022854974 cites W2091715846 @default.
- W2022854974 cites W2108539842 @default.
- W2022854974 cites W2112269107 @default.
- W2022854974 cites W2131911297 @default.
- W2022854974 cites W2133663178 @default.
- W2022854974 cites W2134120396 @default.
- W2022854974 cites W2135848009 @default.
- W2022854974 cites W2138204526 @default.
- W2022854974 cites W2256578114 @default.
- W2022854974 cites W2479500547 @default.
- W2022854974 cites W4252713891 @default.
- W2022854974 cites W91671232 @default.
- W2022854974 doi "https://doi.org/10.1007/s12008-014-0249-9" @default.
- W2022854974 hasPublicationYear "2014" @default.
- W2022854974 type Work @default.
- W2022854974 sameAs 2022854974 @default.
- W2022854974 citedByCount "2" @default.
- W2022854974 countsByYear W20228549742015 @default.
- W2022854974 countsByYear W20228549742022 @default.
- W2022854974 crossrefType "journal-article" @default.
- W2022854974 hasAuthorship W2022854974A5007985159 @default.
- W2022854974 hasAuthorship W2022854974A5016267951 @default.
- W2022854974 hasAuthorship W2022854974A5016771293 @default.
- W2022854974 hasAuthorship W2022854974A5026669578 @default.
- W2022854974 hasAuthorship W2022854974A5065987514 @default.
- W2022854974 hasAuthorship W2022854974A5069420524 @default.
- W2022854974 hasBestOaLocation W20228549742 @default.
- W2022854974 hasConcept C11413529 @default.
- W2022854974 hasConcept C114614502 @default.
- W2022854974 hasConcept C151876577 @default.
- W2022854974 hasConcept C154945302 @default.
- W2022854974 hasConcept C165464430 @default.
- W2022854974 hasConcept C165818556 @default.
- W2022854974 hasConcept C184720557 @default.
- W2022854974 hasConcept C2524010 @default.
- W2022854974 hasConcept C2778626561 @default.
- W2022854974 hasConcept C31487907 @default.
- W2022854974 hasConcept C33923547 @default.
- W2022854974 hasConcept C41008148 @default.
- W2022854974 hasConcept C54829058 @default.
- W2022854974 hasConcept C70518039 @default.
- W2022854974 hasConceptScore W2022854974C11413529 @default.
- W2022854974 hasConceptScore W2022854974C114614502 @default.
- W2022854974 hasConceptScore W2022854974C151876577 @default.
- W2022854974 hasConceptScore W2022854974C154945302 @default.
- W2022854974 hasConceptScore W2022854974C165464430 @default.
- W2022854974 hasConceptScore W2022854974C165818556 @default.
- W2022854974 hasConceptScore W2022854974C184720557 @default.
- W2022854974 hasConceptScore W2022854974C2524010 @default.
- W2022854974 hasConceptScore W2022854974C2778626561 @default.
- W2022854974 hasConceptScore W2022854974C31487907 @default.
- W2022854974 hasConceptScore W2022854974C33923547 @default.
- W2022854974 hasConceptScore W2022854974C41008148 @default.
- W2022854974 hasConceptScore W2022854974C54829058 @default.
- W2022854974 hasConceptScore W2022854974C70518039 @default.
- W2022854974 hasIssue "4" @default.
- W2022854974 hasLocation W20228549741 @default.
- W2022854974 hasLocation W20228549742 @default.
- W2022854974 hasLocation W20228549743 @default.
- W2022854974 hasLocation W20228549744 @default.
- W2022854974 hasLocation W20228549745 @default.
- W2022854974 hasOpenAccess W2022854974 @default.
- W2022854974 hasPrimaryLocation W20228549741 @default.
- W2022854974 hasRelatedWork W1491408434 @default.
- W2022854974 hasRelatedWork W1562785334 @default.
- W2022854974 hasRelatedWork W1672741271 @default.
- W2022854974 hasRelatedWork W2055314463 @default.
- W2022854974 hasRelatedWork W2113890162 @default.
- W2022854974 hasRelatedWork W2349993536 @default.
- W2022854974 hasRelatedWork W2383288821 @default.
- W2022854974 hasRelatedWork W3170162598 @default.