Augmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Clouds

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dc.contributor.authorJelínek, Alešcs
dc.contributor.authorŽalud, Luděkcs
dc.date.accessioned2022-05-18T14:54:43Z
dc.date.available2022-05-18T14:54:43Z
dc.date.issued2016-07-29cs
dc.description.abstractVectorization is a widely used technique in many areas, mainly in robotics and image processing. Applications in these domains frequently require both speed (for real-time operation) and accuracy (for maximal information gain). This paper proposes an optimization for the high speed vectorization methods, which leads to nearly optimal results. The FTLS algorithm uses the total least squares method for fitting the lines into the point cloud and the presented augmentation for the refinement of the results, is based on a modified Nelder-Mead method. As shown on several experiments, this approach leads to better utilization of the information contained in the point cloud. As a result, the quality of approximation grows steadily with the number of points being vectorized, which was not achieved before. Performance costs are still comparable to the original algorithm, so the real-time operation is not endangered.en
dc.formattextcs
dc.format.extent216-223cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationProceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016) - Volume 2. 2016, p. 216-223.en
dc.identifier.doi10.5220/0005962902160223cs
dc.identifier.isbn978-989-758-198-4cs
dc.identifier.other127074cs
dc.identifier.urihttp://hdl.handle.net/11012/204287
dc.language.isoencs
dc.publisherSciTePresscs
dc.relation.ispartofProceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016) - Volume 2cs
dc.relation.urihttps://www.scitepress.org/Link.aspx?doi=10.5220/0005962902160223cs
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/cs
dc.subjectVectorizationen
dc.subjectPoint Clouden
dc.subjectLinear Regressionen
dc.subjectLeast Squares Fittingen
dc.subjectMobile Roboticsen
dc.titleAugmented Postprocessing of the FTLS Vectorization Algorithm - Approaching to the Globally Optimal Vectorization of the Sorted Point Cloudsen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-127074en
sync.item.dbtypeVAVen
sync.item.insts2022.05.18 16:54:43en
sync.item.modts2022.05.18 16:14:24en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav automatizace a měřicí technikycs
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