Simulated annealing for building roof contours identification from lidar data
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://www.revistaespacios.com/a13v34n01/13340114.html http://hdl.handle.net/11449/76311 |
Resumo: | This paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives. |
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Repositório Institucional da UNESP |
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2946 |
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Simulated annealing for building roof contours identification from lidar dataBuilding roof contoursLiDARSimulated annealingThis paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives.Department of Mathematics Mato Grosso State UniversityDepartment of Cartography São Paulo State UniversityDepartment of Cartography São Paulo State UniversityMato Grosso State UniversityUniversidade Estadual Paulista (Unesp)Galvanin, Edinéia Aparecida dos SantosPoz, Aluir Porfírio Dal [UNESP]2014-05-27T11:30:11Z2014-05-27T11:30:11Z2013-08-21info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://www.revistaespacios.com/a13v34n01/13340114.htmlEspacios, v. 34, n. 1, 2013.0798-1015http://hdl.handle.net/11449/763112-s2.0-848815748222-s2.0-84881574822.pdf50418812042757680000-0002-6678-9599Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEspacios0,144info:eu-repo/semantics/openAccess2024-06-18T15:01:12Zoai:repositorio.unesp.br:11449/76311Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:18:11.683668Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Simulated annealing for building roof contours identification from lidar data |
title |
Simulated annealing for building roof contours identification from lidar data |
spellingShingle |
Simulated annealing for building roof contours identification from lidar data Galvanin, Edinéia Aparecida dos Santos Building roof contours LiDAR Simulated annealing |
title_short |
Simulated annealing for building roof contours identification from lidar data |
title_full |
Simulated annealing for building roof contours identification from lidar data |
title_fullStr |
Simulated annealing for building roof contours identification from lidar data |
title_full_unstemmed |
Simulated annealing for building roof contours identification from lidar data |
title_sort |
Simulated annealing for building roof contours identification from lidar data |
author |
Galvanin, Edinéia Aparecida dos Santos |
author_facet |
Galvanin, Edinéia Aparecida dos Santos Poz, Aluir Porfírio Dal [UNESP] |
author_role |
author |
author2 |
Poz, Aluir Porfírio Dal [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Mato Grosso State University Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Galvanin, Edinéia Aparecida dos Santos Poz, Aluir Porfírio Dal [UNESP] |
dc.subject.por.fl_str_mv |
Building roof contours LiDAR Simulated annealing |
topic |
Building roof contours LiDAR Simulated annealing |
description |
This paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-08-21 2014-05-27T11:30:11Z 2014-05-27T11:30:11Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.revistaespacios.com/a13v34n01/13340114.html Espacios, v. 34, n. 1, 2013. 0798-1015 http://hdl.handle.net/11449/76311 2-s2.0-84881574822 2-s2.0-84881574822.pdf 5041881204275768 0000-0002-6678-9599 |
url |
http://www.revistaespacios.com/a13v34n01/13340114.html http://hdl.handle.net/11449/76311 |
identifier_str_mv |
Espacios, v. 34, n. 1, 2013. 0798-1015 2-s2.0-84881574822 2-s2.0-84881574822.pdf 5041881204275768 0000-0002-6678-9599 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Espacios 0,144 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128631315103744 |