{"id":"https://openalex.org/W3012574980","doi":"https://doi.org/10.1109/tgrs.2020.2995732","title":"Curved Buildings Reconstruction From Airborne LiDAR Data by Matching and Deforming Geometric Primitives","display_name":"Curved Buildings Reconstruction From Airborne LiDAR Data by Matching and Deforming Geometric Primitives","publication_year":2020,"publication_date":"2020-06-08","ids":{"openalex":"https://openalex.org/W3012574980","doi":"https://doi.org/10.1109/tgrs.2020.2995732","mag":"3012574980"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.2995732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2995732","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2003.09934","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jingwei Song","orcid":"https://orcid.org/0000-0003-4438-4627"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Jingwei Song","raw_affiliation_strings":["Center for Autonomous Systems, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-4438-4627","affiliations":[{"raw_affiliation_string":"Center for Autonomous Systems, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shaobo Xia","orcid":"https://orcid.org/0000-0003-2890-838X"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Shaobo Xia","raw_affiliation_strings":["University of Calgary, Calgary, Canada"],"raw_orcid":"https://orcid.org/0000-0003-2890-838X","affiliations":[{"raw_affiliation_string":"University of Calgary, Calgary, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210128053","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":null,"display_name":"Dong Chen","orcid":"https://orcid.org/0000-0001-8118-3889"},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Chen","raw_affiliation_strings":["College of Civil Engineering, Nanjing Forestry University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8118-3889","affiliations":[{"raw_affiliation_string":"College of Civil Engineering, Nanjing Forestry University, Nanjing, China","institution_ids":["https://openalex.org/I167027274"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":1.3622,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.77808401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"59","issue":"2","first_page":"1660","last_page":"1674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.3970000147819519,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.3970000147819519,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.33180001378059387,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.10320000350475311,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8069000244140625},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7759000062942505},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5843999981880188},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.5619000196456909},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.5390999913215637},{"id":"https://openalex.org/keywords/geometric-primitive","display_name":"Geometric primitive","score":0.515500009059906},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5049999952316284},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42570000886917114},{"id":"https://openalex.org/keywords/geometric-modeling","display_name":"Geometric modeling","score":0.42100000381469727},{"id":"https://openalex.org/keywords/solid-modeling","display_name":"Solid modeling","score":0.40220001339912415}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8069000244140625},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7759000062942505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6833000183105469},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5910999774932861},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5843999981880188},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.5619000196456909},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.5390999913215637},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.515500009059906},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5049999952316284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49790000915527344},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.42100000381469727},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.40220001339912415},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.3718000054359436},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C136520226","wikidata":"https://www.wikidata.org/wiki/Q302814","display_name":"Geometric data analysis","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.33799999952316284},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.3231000006198883},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C136428324","wikidata":"https://www.wikidata.org/wiki/Q838414","display_name":"Deformation monitoring","level":3,"score":0.31869998574256897},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C200336642","wikidata":"https://www.wikidata.org/wiki/Q15058706","display_name":"Point set registration","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C29123130","wikidata":"https://www.wikidata.org/wiki/Q874709","display_name":"Computational geometry","level":2,"score":0.2854999899864197},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.27219998836517334},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C56435381","wikidata":"https://www.wikidata.org/wiki/Q1196371","display_name":"Geometric transformation","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2653000056743622},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.2648000121116638}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2020.2995732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2995732","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2003.09934","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.09934","pdf_url":"https://arxiv.org/pdf/2003.09934","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2003.09934","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2003.09934","pdf_url":"https://arxiv.org/pdf/2003.09934","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4813990130","display_name":null,"funder_award_id":"41971415","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1504959567","https://openalex.org/W1516539966","https://openalex.org/W1938204631","https://openalex.org/W1986427369","https://openalex.org/W1987058898","https://openalex.org/W1994881920","https://openalex.org/W2008683230","https://openalex.org/W2020322600","https://openalex.org/W2032618685","https://openalex.org/W2033889706","https://openalex.org/W2035850930","https://openalex.org/W2041170980","https://openalex.org/W2048684659","https://openalex.org/W2051956109","https://openalex.org/W2067751945","https://openalex.org/W2083024210","https://openalex.org/W2092031457","https://openalex.org/W2104525659","https://openalex.org/W2107525000","https://openalex.org/W2110925028","https://openalex.org/W2130722170","https://openalex.org/W2130836867","https://openalex.org/W2144311066","https://openalex.org/W2145618333","https://openalex.org/W2162971901","https://openalex.org/W2205809928","https://openalex.org/W2262036069","https://openalex.org/W2285827343","https://openalex.org/W2461005315","https://openalex.org/W2527142681","https://openalex.org/W2557269700","https://openalex.org/W2567098398","https://openalex.org/W2572207425","https://openalex.org/W2602540228","https://openalex.org/W2624851000","https://openalex.org/W2732510496","https://openalex.org/W2742692613","https://openalex.org/W2768345177","https://openalex.org/W2776645264","https://openalex.org/W2783383390","https://openalex.org/W2785825007","https://openalex.org/W2791756395","https://openalex.org/W2794321690","https://openalex.org/W2801452379","https://openalex.org/W2806124225","https://openalex.org/W2883729355","https://openalex.org/W2948432185","https://openalex.org/W2971497684","https://openalex.org/W3022998786","https://openalex.org/W4246818198","https://openalex.org/W6603406552","https://openalex.org/W6701278468","https://openalex.org/W6711086736"],"related_works":[],"abstract_inverted_index":{"Airborne":[0],"light":[1],"detection":[2],"and":[3,45,159],"ranging":[4],"(LiDAR)":[5],"data":[6,183],"are":[7,54,62],"widely":[8],"applied":[9],"in":[10,17,122,145],"building":[11,41,70],"reconstruction,":[12],"with":[13],"studies":[14],"reporting":[15],"success":[16],"typical":[18],"buildings.":[19],"However,":[20],"the":[21,78,107,111,123,157,177,182],"reconstruction":[22,42,171],"of":[23,161,187],"curved":[24,40,139],"buildings":[25,61,140],"remains":[26],"an":[27,98,169],"open":[28],"research":[29],"problem.":[30],"To":[31,85],"this":[32],"end,":[33],"we":[34,72,89,174],"propose":[35],"a":[36,91],"new":[37,165],"framework":[38,133,179],"for":[39,94],"via":[43,105],"assembling":[44],"deforming":[46],"geometric":[47,66,80],"primitives.":[48,84],"The":[49,131,148,164],"input":[50],"LiDAR":[51,144],"point":[52,112],"clouds":[53],"first":[55],"converted":[56],"into":[57],"contours":[58],"where":[59],"individual":[60],"identified.":[63],"After":[64],"recognizing":[65],"units":[67],"(primitives)":[68],"from":[69],"contours,":[71],"get":[73],"initial":[74,108],"models":[75],"by":[76,118,142],"matching":[77],"basic":[79],"primitives":[81],"to":[82,113,168,185],"these":[83],"polish":[86],"assembly":[87],"models,":[88],"employ":[90],"warping":[92],"field":[93],"model":[95,114],"refinements.":[96],"Specifically,":[97],"embedded":[99],"deformation":[100],"(ED)":[101],"graph":[102,125],"is":[103,116,134],"constructed":[104],"downsampling":[106],"model.":[109],"Then,":[110],"displacements":[115],"minimized":[117],"adjusting":[119],"node":[120],"parameters":[121],"ED":[124],"based":[126],"on":[127,136],"our":[128,162],"objective":[129],"function.":[130],"presented":[132],"validated":[135],"several":[137],"highly":[138],"collected":[141],"various":[143],"different":[146],"cities.":[147],"experimental":[149],"results,":[150],"as":[151,153],"well":[152],"accuracy":[154],"comparison,":[155],"demonstrate":[156],"advantage":[158],"effectiveness":[160],"method.":[163],"insight":[166],"attributes":[167],"efficient":[170],"manner.":[172],"Moreover,":[173],"prove":[175],"that":[176],"primitive-based":[178],"significantly":[180],"reduces":[181],"storage":[184],"10%-20%":[186],"classical":[188],"mesh":[189],"models.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-03-27T00:00:00"}