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Interactive object modelling based on piecewise planar surface patches()

Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object struct...

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Detalles Bibliográficos
Autores principales: Prankl, Johann, Zillich, Michael, Vincze, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3916791/
https://www.ncbi.nlm.nih.gov/pubmed/24511219
http://dx.doi.org/10.1016/j.cviu.2013.01.010
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author Prankl, Johann
Zillich, Michael
Vincze, Markus
author_facet Prankl, Johann
Zillich, Michael
Vincze, Markus
author_sort Prankl, Johann
collection PubMed
description Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms.
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spelling pubmed-39167912014-02-07 Interactive object modelling based on piecewise planar surface patches() Prankl, Johann Zillich, Michael Vincze, Markus Comput Vis Image Underst Article Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms. Academic Press 2013-06 /pmc/articles/PMC3916791/ /pubmed/24511219 http://dx.doi.org/10.1016/j.cviu.2013.01.010 Text en © 2013 Elsevier Inc. 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
Prankl, Johann
Zillich, Michael
Vincze, Markus
Interactive object modelling based on piecewise planar surface patches()
title Interactive object modelling based on piecewise planar surface patches()
title_full Interactive object modelling based on piecewise planar surface patches()
title_fullStr Interactive object modelling based on piecewise planar surface patches()
title_full_unstemmed Interactive object modelling based on piecewise planar surface patches()
title_short Interactive object modelling based on piecewise planar surface patches()
title_sort interactive object modelling based on piecewise planar surface patches()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3916791/
https://www.ncbi.nlm.nih.gov/pubmed/24511219
http://dx.doi.org/10.1016/j.cviu.2013.01.010
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