Using GNG on 3D Object Recognition in Noisy RGB-D data

The object recognition task on 3D scenes is a growing research field that faces some problems relative to the use of 3D point clouds. In this work, we focus on dealing with the noise in the clouds through the use of the Growing Neural Gas (GNG) network filtering algorithm. The GNG method is able to...

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1. autor: Rangel, José Carlos (author)
Kolejni autorzy: Morell, Vicente (author), Cazorla, Miguel (author), Orts-Escolano, Sergio (author), García Rodríguez, José (author)
Format: article
Język:angielski
Wydane: 2019
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Dostęp online:https://ieeexplore.ieee.org/abstract/document/7280353/keywords#keywords
https://ridda2.utp.ac.pa/handle/123456789/9439
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author Rangel, José Carlos
author2 Morell, Vicente
Cazorla, Miguel
Orts-Escolano, Sergio
García Rodríguez, José
author2_role author
author
author
author
author_browse Cazorla, Miguel
García Rodríguez, José
Morell, Vicente
Orts-Escolano, Sergio
Rangel, José Carlos
author_facet Rangel, José Carlos
Morell, Vicente
Cazorla, Miguel
Orts-Escolano, Sergio
García Rodríguez, José
author_role author
collection Repositorio Institucional de documento digitales de acceso abierto de la UTP
dc.creator.none.fl_str_mv Rangel, José Carlos
Morell, Vicente
Cazorla, Miguel
Orts-Escolano, Sergio
García Rodríguez, José
dc.date.none.fl_str_mv 10/01/2015
10/01/2015
2019-12-17T21:09:47Z
2019-12-17T21:09:47Z
2019-12-17T21:09:47Z
2019-12-17T21:09:47Z
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.identifier.none.fl_str_mv https://ieeexplore.ieee.org/abstract/document/7280353/keywords#keywords
2161-4407
https://ridda2.utp.ac.pa/handle/123456789/9439
https://ridda2.utp.ac.pa/handle/123456789/9439
dc.language.none.fl_str_mv eng
en
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
dc.source.none.fl_str_mv reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP
instname:Universidad Tecnológica de Panamá
instacron:U Tecnológica de Panamá
dc.subject.none.fl_str_mv Three-dimensional displays
Robustness
Three-dimensional displays
Robustness
dc.title.none.fl_str_mv Using GNG on 3D Object Recognition in Noisy RGB-D data
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
description The object recognition task on 3D scenes is a growing research field that faces some problems relative to the use of 3D point clouds. In this work, we focus on dealing with the noise in the clouds through the use of the Growing Neural Gas (GNG) network filtering algorithm. The GNG method is able to represent the input data with a desired amount of neurons while preserving the topology of the input space. The selected recognition pipeline works describing extracted keypoints of the clouds, grouping and comparing it to detect the presence of an object in the scene, through a hypothesis verification algorithm. Experiments show how the GNG method yields better recognitions results that others filtering algorithms when noise is present.
eu_rights_str_mv embargoedAccess
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identifier_str_mv 2161-4407
instacron_str U Tecnológica de Panamá
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instname_str Universidad Tecnológica de Panamá
language eng
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publishDate 2019
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reponame_str Repositorio Institucional de documento digitales de acceso abierto de la UTP
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spelling Using GNG on 3D Object Recognition in Noisy RGB-D dataRangel, José CarlosMorell, VicenteCazorla, MiguelOrts-Escolano, SergioGarcía Rodríguez, JoséThree-dimensional displaysRobustnessThree-dimensional displaysRobustnessThe object recognition task on 3D scenes is a growing research field that faces some problems relative to the use of 3D point clouds. In this work, we focus on dealing with the noise in the clouds through the use of the Growing Neural Gas (GNG) network filtering algorithm. The GNG method is able to represent the input data with a desired amount of neurons while preserving the topology of the input space. The selected recognition pipeline works describing extracted keypoints of the clouds, grouping and comparing it to detect the presence of an object in the scene, through a hypothesis verification algorithm. Experiments show how the GNG method yields better recognitions results that others filtering algorithms when noise is present.The object recognition task on 3D scenes is a growing research field that faces some problems relative to the use of 3D point clouds. In this work, we focus on dealing with the noise in the clouds through the use of the Growing Neural Gas (GNG) network filtering algorithm. The GNG method is able to represent the input data with a desired amount of neurons while preserving the topology of the input space. The selected recognition pipeline works describing extracted keypoints of the clouds, grouping and comparing it to detect the presence of an object in the scene, through a hypothesis verification algorithm. Experiments show how the GNG method yields better recognitions results that others filtering algorithms when noise is present.2019-12-17T21:09:47Z2019-12-17T21:09:47Z2019-12-17T21:09:47Z2019-12-17T21:09:47Z10/01/201510/01/2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://ieeexplore.ieee.org/abstract/document/7280353/keywords#keywords2161-4407https://ridda2.utp.ac.pa/handle/123456789/9439https://ridda2.utp.ac.pa/handle/123456789/9439engeninfo:eu-repo/semantics/embargoedAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/94392021-07-06T15:35:00Z
spellingShingle Using GNG on 3D Object Recognition in Noisy RGB-D data
Rangel, José Carlos
Three-dimensional displays
Robustness
Three-dimensional displays
Robustness
status_str publishedVersion
title Using GNG on 3D Object Recognition in Noisy RGB-D data
title_full Using GNG on 3D Object Recognition in Noisy RGB-D data
title_fullStr Using GNG on 3D Object Recognition in Noisy RGB-D data
title_full_unstemmed Using GNG on 3D Object Recognition in Noisy RGB-D data
title_short Using GNG on 3D Object Recognition in Noisy RGB-D data
title_sort Using GNG on 3D Object Recognition in Noisy RGB-D data
topic Three-dimensional displays
Robustness
Three-dimensional displays
Robustness
url https://ieeexplore.ieee.org/abstract/document/7280353/keywords#keywords
https://ridda2.utp.ac.pa/handle/123456789/9439