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On the search of optimal reconstruction resolution

In this paper we present a novel algorithm to optimize the reconstruction from non-uniform point sets. We introduce a statistically-derived topology-controller for selecting the reconstruction resolution of a given non-uniform point set. Deriving information from homology-based statistics, our topol...

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Detalles Bibliográficos
Autores principales: Vuçini, Erald, Kropatsch, Walter G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3401991/
https://www.ncbi.nlm.nih.gov/pubmed/22865947
http://dx.doi.org/10.1016/j.patrec.2011.10.006
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author Vuçini, Erald
Kropatsch, Walter G.
author_facet Vuçini, Erald
Kropatsch, Walter G.
author_sort Vuçini, Erald
collection PubMed
description In this paper we present a novel algorithm to optimize the reconstruction from non-uniform point sets. We introduce a statistically-derived topology-controller for selecting the reconstruction resolution of a given non-uniform point set. Deriving information from homology-based statistics, our topology-controller ensures a stable and sound basis for the analysis process. By analyzing our topology-controller, we select an optimal reconstruction resolution which ensures both low reconstruction errors and a topological stability of the underlying signal. Our approach offers a valuable method for the evaluation of the reconstruction process without the need of visual inspection of the reconstructed datasets. By means of qualitative results we show how our proposed topology statistics provides complementary information in the enhancement of existing reconstruction pipelines in visualization.
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spelling pubmed-34019912012-08-01 On the search of optimal reconstruction resolution Vuçini, Erald Kropatsch, Walter G. Pattern Recognit Lett Article In this paper we present a novel algorithm to optimize the reconstruction from non-uniform point sets. We introduce a statistically-derived topology-controller for selecting the reconstruction resolution of a given non-uniform point set. Deriving information from homology-based statistics, our topology-controller ensures a stable and sound basis for the analysis process. By analyzing our topology-controller, we select an optimal reconstruction resolution which ensures both low reconstruction errors and a topological stability of the underlying signal. Our approach offers a valuable method for the evaluation of the reconstruction process without the need of visual inspection of the reconstructed datasets. By means of qualitative results we show how our proposed topology statistics provides complementary information in the enhancement of existing reconstruction pipelines in visualization. Elsevier Science 2012-08-01 /pmc/articles/PMC3401991/ /pubmed/22865947 http://dx.doi.org/10.1016/j.patrec.2011.10.006 Text en © 2012 Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/3.0/ Open Access under CC BY-NC-ND 3.0 (https://creativecommons.org/licenses/by-nc-nd/3.0/) license
spellingShingle Article
Vuçini, Erald
Kropatsch, Walter G.
On the search of optimal reconstruction resolution
title On the search of optimal reconstruction resolution
title_full On the search of optimal reconstruction resolution
title_fullStr On the search of optimal reconstruction resolution
title_full_unstemmed On the search of optimal reconstruction resolution
title_short On the search of optimal reconstruction resolution
title_sort on the search of optimal reconstruction resolution
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3401991/
https://www.ncbi.nlm.nih.gov/pubmed/22865947
http://dx.doi.org/10.1016/j.patrec.2011.10.006
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