Parametric curve reconstruction from point clouds using minimization techniques
dc.contributor.author | Ruiz, O.E. | |
dc.contributor.author | Cortés, C. | |
dc.contributor.author | Aristizábal, M. | |
dc.contributor.author | Acosta, D.A. | |
dc.contributor.author | Vanegas, C.A. | |
dc.contributor.department | Universidad EAFIT. Departamento de Ingeniería Mecánica | spa |
dc.contributor.researchgroup | Laboratorio CAD/CAM/CAE | spa |
dc.date.accessioned | 2021-04-16T21:24:55Z | |
dc.date.available | 2021-04-16T21:24:55Z | |
dc.date.issued | 2013-01-01 | |
dc.description.abstract | Curve reconstruction from noisy point samples is central to surface reconstruction and therefore to reverse engineering, medical imaging, etc. Although Piecewise Linear (PL) curve reconstruction plays an important role, smooth (C1-, C2-,?) curves are needed for many applications. In reconstruction of parametric curves from noisy point samples there remain unsolved issues such as (1) high computational expenses, (2) presence of artifacts and outlier curls, (3) erratic behavior of self-intersecting curves, and (4) erratic excursions at sharp corners. Some of these issues are related to non-Nyquist (i.e. sparse) samples. In response to these shortcomings, this article reports the minimization-based fitting of parametric curves for noisy point clouds. Our approach features: (a) Principal Component Analysis (PCA) pre-processing to obtain a topologically correct approximation of the sampled curve. (b) Numerical, instead of algebraic, calculation of roots in point-to-curve distances. (c) Penalties for curve excursions by using point cloud to - curve and curve to point cloud. (d) Objective functions which are economic to minimize. The implemented algorithms successfully deal with self - intersecting and / or non-Nyquist samples. Ongoing research includes self-tuning of the algorithms and decimation of the point cloud and the control polygon. | eng |
dc.identifier | https://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=2388 | |
dc.identifier.isbn | 9789898565464 | |
dc.identifier.other | SCOPUS;2-s2.0-84878152042 | |
dc.identifier.uri | http://hdl.handle.net/10784/29492 | |
dc.language.iso | eng | spa |
dc.relation.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878152042&partnerID=40&md5=f7b1780809af1487d723ac2543ab9171 | |
dc.source | Parametric Curve Reconstruction From Point Clouds Using Minimization Techniques | |
dc.subject.keyword | Computational expense | eng |
dc.subject.keyword | Control polygons | eng |
dc.subject.keyword | Curve reconstruction | eng |
dc.subject.keyword | Minimization techniques | eng |
dc.subject.keyword | Noisy point | eng |
dc.subject.keyword | Objective functions | eng |
dc.subject.keyword | Parametric curve | eng |
dc.subject.keyword | Self-intersecting curves | eng |
dc.subject.keyword | Algorithms | eng |
dc.subject.keyword | Computer graphics | eng |
dc.subject.keyword | Information analysis | eng |
dc.subject.keyword | Information systems | eng |
dc.subject.keyword | Medical imaging | eng |
dc.subject.keyword | Optimization | eng |
dc.subject.keyword | Piecewise linear techniques | eng |
dc.subject.keyword | Principal component analysis | eng |
dc.subject.keyword | Reverse engineering | eng |
dc.subject.keyword | Curve fitting | eng |
dc.title | Parametric curve reconstruction from point clouds using minimization techniques | eng |
dc.type | info:eu-repo/semantics/conferencePaper | eng |
dc.type | conferencePaper | eng |
dc.type | info:eu-repo/semantics/publishedVersion | eng |
dc.type | publishedVersion | eng |
dc.type.local | Documento de conferencia | spa |