{"id":"https://openalex.org/W2081780340","doi":"https://doi.org/10.1109/tits.2015.2399492","title":"Automated Extraction of Urban Road Facilities Using Mobile Laser Scanning Data","display_name":"Automated Extraction of Urban Road Facilities Using Mobile Laser Scanning Data","publication_year":2015,"publication_date":"2015-02-24","ids":{"openalex":"https://openalex.org/W2081780340","doi":"https://doi.org/10.1109/tits.2015.2399492","mag":"2081780340"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2015.2399492","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2015.2399492","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065937604","display_name":"Yongtao Yu","orcid":"https://orcid.org/0000-0001-7204-9346"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongtao Yu","raw_affiliation_strings":["Fujian Key Laboratory of Sensing and Computing for Smart Cities, Xiamen University, Xiamen, China","[Fujian Key Lab. of Sensing & Comput. for Smart Cities, Xiamen Univ., Xiamen, China]"],"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Sensing and Computing for Smart Cities, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"[Fujian Key Lab. of Sensing & Comput. for Smart Cities, Xiamen Univ., Xiamen, China]","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613889","display_name":"Jonathan Li","orcid":"https://orcid.org/0000-0001-7899-0049"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]},{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Jonathan Li","raw_affiliation_strings":["Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (MOE), University of Waterloo, Waterloo, ON, Canada","Key Lab. of Underwater Acoust. Commun., Xiamen Univ., Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Underwater Acoustic Communication and Marine Information Technology (MOE), University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Key Lab. of Underwater Acoust. Commun., Xiamen Univ., Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035056634","display_name":"Haiyan Guan","orcid":"https://orcid.org/0000-0003-3691-8721"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyan Guan","raw_affiliation_strings":["College of Geography and Remote Sensing, Nanjing University of Information Science and Technology, Nanjing, 210044, China","Coll. of Geogr. & Remote Sensing, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Geography and Remote Sensing, Nanjing University of Information Science and Technology, Nanjing, 210044, China","institution_ids":["https://openalex.org/I200845125"]},{"raw_affiliation_string":"Coll. of Geogr. & Remote Sensing, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100416961","display_name":"Cheng Wang","orcid":"https://orcid.org/0000-0001-6075-796X"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Wang","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065937604"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":7.2666,"has_fulltext":false,"cited_by_count":98,"citation_normalized_percentile":{"value":0.97239644,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"16","issue":"4","first_page":"2167","last_page":"2181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/correctness","display_name":"Correctness","score":0.70843106508255},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5570366382598877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5456625819206238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5280697345733643},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.5270479321479797},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49659234285354614},{"id":"https://openalex.org/keywords/laser-scanning","display_name":"Laser scanning","score":0.4917784035205841},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.46580037474632263},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4141281247138977},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32707756757736206},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24970892071723938},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1964302659034729},{"id":"https://openalex.org/keywords/laser","display_name":"Laser","score":0.11214357614517212}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.70843106508255},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5570366382598877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5456625819206238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5280697345733643},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.5270479321479797},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49659234285354614},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.4917784035205841},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.46580037474632263},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4141281247138977},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32707756757736206},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24970892071723938},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1964302659034729},{"id":"https://openalex.org/C520434653","wikidata":"https://www.wikidata.org/wiki/Q38867","display_name":"Laser","level":2,"score":0.11214357614517212},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2015.2399492","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2015.2399492","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8100000023841858,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W30263738","https://openalex.org/W48960425","https://openalex.org/W52592340","https://openalex.org/W1977494291","https://openalex.org/W1979880452","https://openalex.org/W1988193150","https://openalex.org/W2000035714","https://openalex.org/W2002556620","https://openalex.org/W2007575046","https://openalex.org/W2013442102","https://openalex.org/W2020405049","https://openalex.org/W2022394120","https://openalex.org/W2023056405","https://openalex.org/W2027087416","https://openalex.org/W2027781877","https://openalex.org/W2033943689","https://openalex.org/W2043543487","https://openalex.org/W2045388733","https://openalex.org/W2047393497","https://openalex.org/W2055102868","https://openalex.org/W2057897173","https://openalex.org/W2066481472","https://openalex.org/W2071753994","https://openalex.org/W2074437835","https://openalex.org/W2075597533","https://openalex.org/W2077506631","https://openalex.org/W2079589066","https://openalex.org/W2090800226","https://openalex.org/W2098969453","https://openalex.org/W2105591368","https://openalex.org/W2105996029","https://openalex.org/W2106896169","https://openalex.org/W2117645012","https://openalex.org/W2121947440","https://openalex.org/W2122422695","https://openalex.org/W2124870279","https://openalex.org/W2127642098","https://openalex.org/W2127911825","https://openalex.org/W2131531901","https://openalex.org/W2136651098","https://openalex.org/W2137176344","https://openalex.org/W2148254631","https://openalex.org/W2154980168","https://openalex.org/W2157712010","https://openalex.org/W2160392092","https://openalex.org/W2160821342","https://openalex.org/W2162401076","https://openalex.org/W2173758409","https://openalex.org/W2185848344","https://openalex.org/W4285719527","https://openalex.org/W6601946194","https://openalex.org/W6668690678","https://openalex.org/W6675944681","https://openalex.org/W6686591470"],"related_works":["https://openalex.org/W3008339103","https://openalex.org/W2404647514","https://openalex.org/W1667647204","https://openalex.org/W4247536566","https://openalex.org/W3119814709","https://openalex.org/W2018477250","https://openalex.org/W1508895727","https://openalex.org/W4241418540","https://openalex.org/W2725786787","https://openalex.org/W4283160672"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,43,58,91,98],"novel,":[4],"automated":[5,156],"algorithm":[6,33,118,154],"for":[7,22,155],"rapidly":[8],"extracting":[9,135],"urban":[10,161],"road":[11,162],"facilities,":[12],"including":[13],"street":[14],"light":[15,137],"poles,":[16,138],"traffic":[17,139],"signposts,":[18,140],"and":[19,28,75,84,125,131,141,149,157],"bus":[20,142],"stations,":[21],"transportation-related":[23],"applications.":[24],"A":[25],"detailed":[26],"description":[27],"implementation":[29],"of":[30,53,109,127,151,160],"the":[31,51,107,116,147,152],"proposed":[32,117,153],"is":[34,64,103],"provided":[35],"using":[36],"mobile":[37],"laser":[38],"scanning":[39],"data":[40,54],"collected":[41],"by":[42],"state-of-the-art":[44],"RIEGL":[45],"VMX-450":[46],"system.":[47],"First,":[48],"to":[49,55,66,105],"reduce":[50],"quantity":[52],"be":[56],"handled,":[57],"fast":[59],"voxel-based":[60,85],"upward":[61],"growing":[62],"method":[63],"developed":[65,104],"remove":[67],"ground":[68],"points.":[69],"Then,":[70],"off-ground":[71],"points":[72],"are":[73],"clustered":[74],"segmented":[76],"into":[77],"individual":[78],"objects":[79],"via":[80],"Euclidean":[81],"distance":[82],"clustering":[83],"normalized":[86],"cut":[87],"segmentation,":[88],"respectively.":[89],"Finally,":[90],"3-D":[92,110,136],"object":[93],"matching":[94],"framework,":[95],"benefiting":[96],"from":[97],"locally":[99],"affine-invariant":[100],"geometric":[101],"constraint,":[102],"achieve":[106],"extraction":[108,159],"objects.":[111],"Quantitative":[112],"evaluations":[113],"show":[114],"that":[115],"attains":[119],"an":[120],"average":[121],"completeness,":[122],"correctness,":[123],"quality,":[124],"F1-measure":[126],"0.949,":[128],"0.971,":[129],"0.922,":[130],"0.960,":[132],"respectively,":[133],"in":[134],"stations.":[143],"Comparative":[144],"studies":[145],"demonstrate":[146],"efficiency":[148],"feasibility":[150],"rapid":[158],"facilities.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}