{"id":"https://openalex.org/W4293794985","doi":"https://doi.org/10.1109/access.2022.3202223","title":"Automatic Label Injection Into Local Infrastructure LiDAR Point Cloud for Training Data Set Generation","display_name":"Automatic Label Injection Into Local Infrastructure LiDAR Point Cloud for Training Data Set Generation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4293794985","doi":"https://doi.org/10.1109/access.2022.3202223"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3202223","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3202223","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09868338.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09868338.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069953604","display_name":"Zsolt Vincze","orcid":"https://orcid.org/0000-0002-5813-3530"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Zsolt Vincze","raw_affiliation_strings":["Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest, Hungary","Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Stoczek str. 6. J. building fifth floor, Budapest, Hungary"],"raw_orcid":"https://orcid.org/0000-0002-5813-3530","affiliations":[{"raw_affiliation_string":"Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Stoczek str. 6. J. building fifth floor, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011155695","display_name":"Andr\u00e1s R\u00f6vid","orcid":"https://orcid.org/0000-0002-9044-1760"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Andras Rovid","raw_affiliation_strings":["Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest, Hungary","Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Stoczek str. 6. J. building fifth floor, Budapest, Hungary"],"raw_orcid":"https://orcid.org/0000-0002-9044-1760","affiliations":[{"raw_affiliation_string":"Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Stoczek str. 6. J. building fifth floor, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004821327","display_name":"Viktor Tihanyi","orcid":"https://orcid.org/0000-0002-0526-5986"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Viktor Tihanyi","raw_affiliation_strings":["Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest, Hungary","Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Stoczek str. 6. J. building fifth floor, Budapest, Hungary"],"raw_orcid":"https://orcid.org/0000-0002-0526-5986","affiliations":[{"raw_affiliation_string":"Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Stoczek str. 6. J. building fifth floor, Budapest, Hungary","institution_ids":["https://openalex.org/I29770179"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2597,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.48940449,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"10","issue":null,"first_page":"91213","last_page":"91226"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7086480855941772},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.655510663986206},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5998092889785767},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5052686333656311},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.47946131229400635},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4665778577327728},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4580177366733551},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.41673150658607483},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.27616673707962036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19935137033462524},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10711333155632019},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07646071910858154}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7086480855941772},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.655510663986206},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5998092889785767},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5052686333656311},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.47946131229400635},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4665778577327728},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4580177366733551},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.41673150658607483},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.27616673707962036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19935137033462524},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10711333155632019},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07646071910858154},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3202223","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3202223","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09868338.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:19ba306bf9bd4b1fbbff942a2d327517","is_oa":true,"landing_page_url":"https://doaj.org/article/19ba306bf9bd4b1fbbff942a2d327517","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 91213-91226 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3202223","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3202223","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09868338.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G4368342600","display_name":null,"funder_award_id":"TKP2020","funder_id":"https://openalex.org/F4320311358","funder_display_name":"Budapesti M\u0171szaki \u00e9s Gazdas\u00e1gtudom\u00e1nyi Egyetem"},{"id":"https://openalex.org/G6420385980","display_name":null,"funder_award_id":"TKP2020","funder_id":"https://openalex.org/F4320328991","funder_display_name":"Innov\u00e1ci\u00f3s \u00e9s Technol\u00f3giai Miniszt\u00e9rium"},{"id":"https://openalex.org/G7269143174","display_name":null,"funder_award_id":"TKP2020","funder_id":"https://openalex.org/F4320326762","funder_display_name":"Nemzeti Kutat\u00e1si Fejleszt\u00e9si \u00e9s Innov\u00e1ci\u00f3s Hivatal"}],"funders":[{"id":"https://openalex.org/F4320311358","display_name":"Budapesti M\u0171szaki \u00e9s Gazdas\u00e1gtudom\u00e1nyi Egyetem","ror":"https://ror.org/02w42ss30"},{"id":"https://openalex.org/F4320326762","display_name":"Nemzeti Kutat\u00e1si Fejleszt\u00e9si \u00e9s Innov\u00e1ci\u00f3s Hivatal","ror":null},{"id":"https://openalex.org/F4320328991","display_name":"Innov\u00e1ci\u00f3s \u00e9s Technol\u00f3giai Miniszt\u00e9rium","ror":"https://ror.org/02ey3ab96"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4293794985.pdf","grobid_xml":"https://content.openalex.org/works/W4293794985.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1995963656","https://openalex.org/W2107528150","https://openalex.org/W2150066425","https://openalex.org/W2154458843","https://openalex.org/W2167667767","https://openalex.org/W2170715240","https://openalex.org/W2946113904","https://openalex.org/W2946639796","https://openalex.org/W2955189650","https://openalex.org/W2968296999","https://openalex.org/W3004135102","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3037058446","https://openalex.org/W3105126405","https://openalex.org/W3114281349","https://openalex.org/W3119659463","https://openalex.org/W3134298700","https://openalex.org/W4221141829","https://openalex.org/W4285813083","https://openalex.org/W4312253363","https://openalex.org/W6760782946","https://openalex.org/W6771941581","https://openalex.org/W6780503301"],"related_works":["https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W2786391746","https://openalex.org/W2991483587","https://openalex.org/W4381430104","https://openalex.org/W2995102745","https://openalex.org/W4226059458","https://openalex.org/W2914559142","https://openalex.org/W1990237101","https://openalex.org/W3196471634"],"abstract_inverted_index":{"The":[0,119],"representation":[1],"of":[2,13,17,23,85,95,154],"objects":[3,80],"in":[4,81,114,133,211],"LiDAR":[5,89],"point":[6,83],"clouds":[7],"is":[8,54,75,168,172],"changed":[9],"as":[10],"the":[11,14,24,43,52,56,79,82,86,93,107,117,152,190,198,212,221,231],"height":[12,104],"mounting":[15],"position":[16],"sensor":[18,53,90,131,245],"devices":[19],"gets":[20],"increased.":[21],"Most":[22],"available":[25,146],"open":[26],"datasets":[27,48],"for":[28,147,164],"training":[29,184],"machine":[30,176],"learning":[31,177],"based":[32,91,178],"object":[33],"detectors":[34,44],"are":[35],"generated":[36,196,227],"with":[37],"vehicle":[38,242],"top":[39,243],"mounted":[40,244],"sensors,":[41],"thus":[42],"trained":[45,180,240],"on":[46,92,127,181,193,223,241],"such":[47],"perform":[49],"weaker":[50],"when":[51],"observing":[55],"scene":[57],"from":[58],"a":[59,69,96,128,134,155,160,175,194,208,238],"significantly":[60],"higher":[61],"viewpoint":[62,224],"(e.g.":[63],"infrastructure":[64,88],"sensor).":[65],"In":[66],"this":[67],"paper":[68],"novel":[70],"Automatic":[71,200],"Label":[72,201],"Injection":[73,202],"method":[74],"proposed":[76,120,199,232],"to":[77,189,205,237],"label":[78,233],"cloud":[84],"high-mounted":[87],"output":[94],"well":[97],"performing":[98],"“trainer”":[99],"detector":[100,179,191,222,239],"deployed":[101],"at":[102],"optimal":[103],"while":[105],"considering":[106],"uncertainties":[108],"caused":[109],"by":[110,197,219,230],"various":[111],"factors":[112],"described":[113],"detail":[115],"throughout":[116],"paper.":[118],"automatic":[121,165],"labeling":[122],"approach":[123],"has":[124],"been":[125],"validated":[126],"small":[129],"scale":[130],"setup":[132],"real-world":[135],"traffic":[136],"scenario":[137],"where":[138,144],"accurate":[139],"differential":[140,182],"GNSS":[141],"reference":[142],"data":[143,226],"also":[145,169],"each":[148],"test":[149],"vehicle.":[150],"Furthermore,":[151],"concept":[153],"distributed":[156],"multi-sensor":[157],"system":[158],"covering":[159],"larger":[161],"area":[162],"aimed":[163],"dataset":[166,185,195],"generation":[167],"presented.":[170],"It":[171],"shown":[173],"that":[174],"GNSS-based":[183],"performs":[186],"very":[187],"similarly":[188],"retrained":[192],"technique.":[203],"According":[204],"our":[206],"results":[207],"significant":[209],"increase":[210],"maximum":[213],"detection":[214],"range":[215],"can":[216],"be":[217],"achieved":[218],"retraining":[220],"specific":[225],"fully":[228],"automatically":[229],"injection":[234],"technique":[235],"compared":[236],"data.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}