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基于点云数据的建筑物建模方法 Abstract Buildingmodelingistheprocessofconstructing3Dmodelsofbuildingsusingvarioustechniques.Theemergenceofpointclouddatahashadamassiveimpactonbuildingmodeling,allowingformoreaccurateanddetailedmodelstobecreated.Thispaperpresentsacomprehensivereviewofthestate-of-the-artmethodsforbuildingmodelingusingpointclouddata.Thepaperalsointroducesanovelframeworkthatcombinesmultipletechniquestoenhancetheaccuracyandefficiencyofthemodelingprocess.Theproposedframeworkinvolvesdatapreprocessing,featureextraction,segmentation,andreconstruction,allofwhicharedetailedinthispaper.Theproposedframeworkwastestedonseveralreal-worlddatasetsandcomparedtoexistingmethods.Theresultsshowthattheproposedframeworkoutperformsexistingmethodsintermsofaccuracyandefficiency. Introduction Buildingmodelingplaysanimportantroleinseveralindustries,includingarchitecture,engineering,andconstruction.Buildingmodelsareusedforvisualization,simulation,andanalysisofvariousaspectssuchasstructuralanalysis,energyefficiency,andsafety.Buildingmodelinghastraditionallybeenalabor-intensiveandtime-consumingprocessthatrequiresskilledprofessionals.However,theadventofpointclouddatahasrevolutionizedtheprocessofbuildingmodeling,makingitfasterandmoreaccurate. Pointclouddataisacollectionof3Dpointsthatrepresentthesurfacesofobjectsintherealworld.ThedatacanbeobtainedusingvarioustechniquessuchasLiDAR,photogrammetry,andlaserscanning.Thepointclouddatacanbeuseddirectlyforbuildingmodelingorcanbeprocessedtoextractfeaturesthataidinthemodelingprocess. Thispaperreviewsthestate-of-the-artmethodsforbuildingmodelingusingpointclouddata.Thepaperalsointroducesanovelframeworkthatcombinesmultipletechniquestoimprovetheaccuracyandefficiencyofbuildingmodeling.Theproposedframeworkinvolvespreprocessingthedatatoremovenoiseandoutliers,extractingfeaturesfromthedata,segmentingthedataintomeaningfulcomponents,andfinallyreconstructingthebuildingmodel. RelatedWork Severalmethodshavebeenproposedforbuildingmodelingusingpointclouddata.Thesemethodscanbebr