{"id":"https://openalex.org/W2910924021","doi":"https://doi.org/10.1109/tpami.2019.2893671","title":"Large-Scale Urban Reconstruction with Tensor Clustering and Global Boundary Refinement","display_name":"Large-Scale Urban Reconstruction with Tensor Clustering and Global Boundary Refinement","publication_year":2019,"publication_date":"2019-01-18","ids":{"openalex":"https://openalex.org/W2910924021","doi":"https://doi.org/10.1109/tpami.2019.2893671","mag":"2910924021","pmid":"https://pubmed.ncbi.nlm.nih.gov/30668463"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2019.2893671","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2019.2893671","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/9055268/08618413.pdf","source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/34/9055268/08618413.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084730486","display_name":"Charalambos Poullis","orcid":"https://orcid.org/0000-0001-5666-5026"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Charalambos Poullis","raw_affiliation_strings":["Concordia University, Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5084730486"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":1.2601,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.76377668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"42","issue":"5","first_page":"1132","last_page":"1145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7873272895812988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6898359656333923},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.6073841452598572},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5184235572814941},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4877232015132904},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.48588961362838745},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.454714298248291},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43626081943511963},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.4276544153690338},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41489213705062866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39292293787002563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.334001362323761},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19094860553741455},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1546630859375},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.11680659651756287},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09971180558204651},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.09750872850418091}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7873272895812988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6898359656333923},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.6073841452598572},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5184235572814941},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4877232015132904},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.48588961362838745},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.454714298248291},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43626081943511963},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.4276544153690338},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41489213705062866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39292293787002563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.334001362323761},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19094860553741455},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1546630859375},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.11680659651756287},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09971180558204651},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.09750872850418091},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2019.2893671","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2019.2893671","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/9055268/08618413.pdf","source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:30668463","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30668463","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":{"id":"doi:10.1109/tpami.2019.2893671","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2019.2893671","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/9055268/08618413.pdf","source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G4051357290","display_name":null,"funder_award_id":"N01670","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G4107423261","display_name":null,"funder_award_id":"DG-N01670","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"},{"id":"https://openalex.org/G548614812","display_name":null,"funder_award_id":"DND-N01885","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320330045","display_name":"Minist\u00e8re de la D\u00e9fense Nationale","ror":"https://ror.org/035rreb34"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2910924021.pdf","grobid_xml":"https://content.openalex.org/works/W2910924021.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1571051704","https://openalex.org/W1580065766","https://openalex.org/W1592510033","https://openalex.org/W1981934656","https://openalex.org/W2006502673","https://openalex.org/W2007492000","https://openalex.org/W2012494417","https://openalex.org/W2023657303","https://openalex.org/W2033889706","https://openalex.org/W2036835491","https://openalex.org/W2054658115","https://openalex.org/W2065429801","https://openalex.org/W2093058919","https://openalex.org/W2107732308","https://openalex.org/W2114816128","https://openalex.org/W2123271629","https://openalex.org/W2127310338","https://openalex.org/W2132480024","https://openalex.org/W2152654418","https://openalex.org/W2159075734","https://openalex.org/W2166334548","https://openalex.org/W2166430258","https://openalex.org/W6634282858","https://openalex.org/W6673790229","https://openalex.org/W6684730797"],"related_works":["https://openalex.org/W4367313141","https://openalex.org/W2004086023","https://openalex.org/W2733999579","https://openalex.org/W2110217573","https://openalex.org/W4283374591","https://openalex.org/W2910751785","https://openalex.org/W4390100400","https://openalex.org/W4366547507","https://openalex.org/W4362512700","https://openalex.org/W2074396925"],"abstract_inverted_index":{"Accurate":[0],"and":[1,16,37,46,97,146,217,229],"efficient":[2],"methods":[3,195],"for":[4,31,59,73,163,225],"large-scale":[5],"urban":[6],"reconstruction":[7],"are":[8,94,156,220],"of":[9,200],"significant":[10,205],"importance":[11],"to":[12,53,99,121,167],"the":[13,54,104,107,123,137,171,218,239,242],"computer":[14,17],"vision":[15],"graphics":[18],"communities.":[19],"Although":[20],"rapid":[21],"acquisition":[22],"techniques":[23],"such":[24,42],"as":[25,185],"airborne":[26],"LiDAR":[27,77],"have":[28,191],"been":[29],"around":[30],"many":[32],"years,":[33],"creating":[34],"a":[35,70,160,173,186],"useful":[36],"functional":[38],"virtual":[39],"environment":[40],"from":[41,170],"data":[43,60,78,86,144],"remains":[44],"difficult":[45],"labor":[47],"intensive.":[48],"This":[49],"is":[50,87,110,119,179],"due":[51],"largely":[52],"necessity":[55],"in":[56,207],"present":[57,69],"solutions":[58],"dependent":[61],"user":[62],"defined":[63],"parameters.":[64],"In":[65],"this":[66,183],"paper":[67],"we":[68],"new":[71,174],"solution":[72],"automatically":[74],"converting":[75],"large":[76],"pointcloud":[79,198],"into":[80,90,112,125],"simplified":[81],"polygonal":[82],"3D":[83],"models.":[84],"The":[85,153,222],"first":[88],"divided":[89],"smaller":[91],"components":[92],"which":[93,203],"processed":[95],"independently":[96],"concurrently":[98],"extract":[100,168],"various":[101],"metrics":[102],"about":[103],"points.":[105],"Next,":[106],"extracted":[108],"information":[109],"converted":[111],"tensors.":[113],"A":[114],"robust":[115],"agglomerate":[116],"clustering":[117,140,228],"algorithm":[118],"proposed":[120,138],"segment":[122],"tensors":[124],"clusters":[126,172],"representing":[127],"geospatial":[128,208],"objects":[129],"e.g.,":[130,210],"roads,":[131],"buildings,":[132],"etc.":[133],"Unlike":[134],"previous":[135],"methods,":[136],"tensor":[139,227],"process":[141,178],"has":[142],"no":[143],"dependencies":[145],"does":[147],"not":[148],"require":[149],"any":[150],"user-defined":[151],"parameter.":[152],"required":[154],"parameters":[155],"adaptively":[157],"computed":[158],"assuming":[159],"Weibull":[161],"distribution":[162],"similarity":[164],"distances.":[165],"Lastly,":[166],"boundaries":[169],"multi-stage":[175],"boundary":[176,231],"refinement":[177,232],"developed":[180],"by":[181],"reformulating":[182],"extraction":[184],"global":[187,230],"optimization":[188],"problem.":[189],"We":[190],"extensively":[192],"tested":[193],"our":[194],"on":[196,241],"several":[197],"datasets":[199],"different":[201],"resolutions":[202],"exhibit":[204],"variability":[206],"characteristics":[209],"ground":[211],"surface":[212],"inclination,":[213],"building":[214],"density,":[215],"etc":[216],"results":[219],"reported.":[221],"source":[223],"code":[224],"both":[226],"will":[233],"be":[234],"made":[235],"publicly":[236],"available":[237],"with":[238],"publication":[240],"author's":[243],"website.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-23T13:55:30.953635","created_date":"2025-10-10T00:00:00"}
