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dc.contributor.authorMarcato Fernandes, Vanessa Jordao [UNESP]
dc.contributor.authorDal Poz, Aluir Porfirio [UNESP]
dc.date.accessioned2018-11-26T17:15:38Z
dc.date.available2018-11-26T17:15:38Z
dc.date.issued2016-12-01
dc.identifierhttp://dx.doi.org/10.1109/JSTARS.2016.2601068
dc.identifier.citationIeee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 9, n. 12, p. 5493-5505, 2016.
dc.identifier.issn1939-1404
dc.identifier.urihttp://hdl.handle.net/11449/162325
dc.description.abstractThis paper proposes a method for extracting groups of straight lines that represent roof boundary sides and roof ridgelines from high-resolution aerial images using corresponding airborne laser scanner (ALS) roof polyhedrons as initial approximations. Our motivation for this research is the possibility of future use of resulting image-space straight lines in several applications. For example, straight lines that represent roof boundary sides and precisely extracted from a high-resolution image can be back-projected onto the ALS-derived building polyhedron for refining the accuracy of its boundary. The proposed method is based on two main steps. First, straight lines that are candidates to represent roof ridgelines and roof boundary sides of a building are extracted from the aerial image. The ALS-derived roof boundary sides and roof ridgelines are projected onto the image space, and bolding boxes are constructed around the projected straight lines while considering the projection errors. This allows the extraction of straight lines within the bounding boxes. Second, a group of straight lines that represent roof boundary sides and roof ridgelines of a selected building is obtained through the optimization of a Markov random field-based energy function using the genetic algorithm optimization method. The formulation of this energy function considers several attributes, such as the proximity of the extracted straight lines to the corresponding projected ALS-derived roof polyhedron and the rectangularity (extracted straight lines that intersect at nearly 90 degrees). In order to validate the proposed method, four experiments were accomplished using high-resolution aerial images, along with interior and exterior orientation parameters, and available ALS-derived building roof polyhedrons. The obtained results have shown that the method works properly and this will be qualitatively and quantitatively demonstrated in this research.en
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.format.extent5493-5505
dc.language.isoeng
dc.publisherIeee-inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing
dc.sourceWeb of Science
dc.subjectAirborne laser scanner (ALS)
dc.subjectMarkov random field (MRF)
dc.subjectstraight line
dc.titleA Markov-Random-Field Approach for Extracting Straight-Line Segments of Roofs From High-Resolution Aerial Imagesen
dc.typeArtigo
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee-inst Electrical Electronics Engineers Inc
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.description.affiliationSao Paulo State Univ, BR-19060900 Presidente Prudente, Brazil
dc.description.affiliationSao Paulo State Univ, Dept Cartog, BR-19060900 Presidente Prudente, Brazil
dc.description.affiliationUnespSao Paulo State Univ, BR-19060900 Presidente Prudente, Brazil
dc.description.affiliationUnespSao Paulo State Univ, Dept Cartog, BR-19060900 Presidente Prudente, Brazil
dc.identifier.doi10.1109/JSTARS.2016.2601068
dc.identifier.wosWOS:000391468100020
dc.rights.accessRightsAcesso aberto
dc.description.sponsorshipIdFAPESP: 2013/13138-0
dc.description.sponsorshipIdFAPESP: 2012/22332-2
dc.description.sponsorshipIdCNPq: 304879/2009-6
dc.identifier.fileWOS000391468100020.pdf
unesp.author.lattes4791496159878691[2]
unesp.author.orcid0000-0002-2534-1229[2]
dc.relation.ispartofsjr1,547
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