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dc.contributor.authorLi, Minglei
dc.contributor.authorNan, Liangliang
dc.contributor.authorLiu, Shaochuang
dc.date.accessioned2016-03-07T12:58:40Z
dc.date.available2016-03-07T12:58:40Z
dc.date.issued2016-02-19
dc.identifier.citationFitting boxes to Manhattan scenes using linear integer programming 2016:1 International Journal of Digital Earth
dc.identifier.issn1753-8947
dc.identifier.issn1753-8955
dc.identifier.doi10.1080/17538947.2016.1143982
dc.identifier.urihttp://hdl.handle.net/10754/600705
dc.description.abstractWe propose an approach for automatic generation of building models by assembling a set of boxes using a Manhattan-world assumption. The method first aligns the point cloud with a per-building local coordinate system, and then fits axis-aligned planes to the point cloud through an iterative regularization process. The refined planes partition the space of the data into a series of compact cubic cells (candidate boxes) spanning the entire 3D space of the input data. We then choose to approximate the target building by the assembly of a subset of these candidate boxes using a binary linear programming formulation. The objective function is designed to maximize the point cloud coverage and the compactness of the final model. Finally, all selected boxes are merged into a lightweight polygonal mesh model, which is suitable for interactive visualization of large scale urban scenes. Experimental results and a comparison with state-of-the-art methods demonstrate the effectiveness of the proposed framework.
dc.language.isoen
dc.publisherInforma UK Limited
dc.relation.urlhttp://www.tandfonline.com/doi/full/10.1080/17538947.2016.1143982
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Digital Earth on 19 Feb 2016, available online: http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1143982.
dc.subjectUrban building models
dc.subjectaerial point cloud
dc.subjectManhattan scenes
dc.subjectlinear integer programming
dc.titleFitting boxes to Manhattan scenes using linear integer programming
dc.typeArticle
dc.contributor.departmentVisual Computing Center (VCC)
dc.identifier.journalInternational Journal of Digital Earth
dc.eprint.versionPost-print
dc.contributor.institutionIntegrated Spatial Information Lab, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, People's Republic of China
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personNan, Liangliang
refterms.dateFOA2017-02-19T00:00:00Z


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