{"id":"https://openalex.org/W3003249290","doi":"https://doi.org/10.1109/iros40897.2019.8967711","title":"Fusing Lidar Data and Aerial Imagery with Perspective Correction for Precise Localization in Urban Canyons","display_name":"Fusing Lidar Data and Aerial Imagery with Perspective Correction for Precise Localization in Urban Canyons","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3003249290","doi":"https://doi.org/10.1109/iros40897.2019.8967711","mag":"3003249290"},"language":"en","primary_location":{"id":"doi:10.1109/iros40897.2019.8967711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8967711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-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/A5011681417","display_name":"Jonghwi Kim","orcid":"https://orcid.org/0000-0001-7484-7982"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jonghwi Kim","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology,Department of Mechanical Engineering,Daejeon,South Korea,34141","Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology,Department of Mechanical Engineering,Daejeon,South Korea,34141","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054727482","display_name":"Jinwhan Kim","orcid":"https://orcid.org/0000-0001-6886-2449"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinwhan Kim","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology,Department of Mechanical Engineering,Daejeon,South Korea,34141","Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology,Department of Mechanical Engineering,Daejeon,South Korea,34141","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3436,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.60879561,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5298","last_page":"5303"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9962999820709229,"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/lidar","display_name":"Lidar","score":0.7989006042480469},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6115750074386597},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6017658710479736},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6003318428993225},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5788943767547607},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.5181164145469666},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5093687772750854},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.49511709809303284},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.48371556401252747},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.463589608669281},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45058438181877136},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4440314471721649},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4412147104740143},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.44047561287879944},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4265109896659851},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3592401146888733},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.25962579250335693},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20851287245750427}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7989006042480469},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6115750074386597},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6017658710479736},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6003318428993225},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5788943767547607},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.5181164145469666},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5093687772750854},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.49511709809303284},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.48371556401252747},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.463589608669281},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45058438181877136},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4440314471721649},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4412147104740143},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.44047561287879944},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4265109896659851},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3592401146888733},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.25962579250335693},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20851287245750427},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros40897.2019.8967711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros40897.2019.8967711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1556911442","https://openalex.org/W1686810756","https://openalex.org/W1821691275","https://openalex.org/W2014001040","https://openalex.org/W2099111195","https://openalex.org/W2107289862","https://openalex.org/W2218718890","https://openalex.org/W2480078828","https://openalex.org/W2601593996","https://openalex.org/W2735449883","https://openalex.org/W2757885920","https://openalex.org/W2799917352","https://openalex.org/W2963311282","https://openalex.org/W2963881378","https://openalex.org/W2963995737","https://openalex.org/W4237347581","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4281783339","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W1964041166","https://openalex.org/W4293094720","https://openalex.org/W2739701376"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"a":[3,69,109,153],"vehicle":[4,140],"localization":[5,85],"method":[6,71],"that":[7],"fuses":[8],"aerial":[9,34,50,104],"maps":[10,51],"and":[11,36,79,91,113,121,141],"lidar":[12,92,119],"data":[13,43],"in":[14,60],"urban":[15,61],"canyon":[16],"environments":[17],"where":[18],"global":[19],"positioning":[20],"system":[21],"(GPS)":[22],"signals":[23],"are":[24,30,38],"inaccurate.":[25],"The":[26],"boundaries":[27,124],"of":[28,102,152,165],"buildings":[29],"extracted":[31],"from":[32],"the":[33,46,88,99,114,118,122,139,143,146,150,163,166],"map":[35,90,144],"they":[37],"matched":[39],"to":[40,72,83,96,127,137,161],"point":[41],"cloud":[42],"provided":[44],"by":[45,86],"lidar.":[47],"However,":[48],"most":[49],"contain":[52],"perspective":[53],"projection":[54,75],"distortions":[55],"which":[56],"can":[57],"be":[58],"significant":[59],"canyons":[62],"with":[63],"tall":[64],"buildings.":[65],"In":[66,94],"this":[67],"study,":[68],"new":[70],"correct":[73],"such":[74],"distortion":[76],"is":[77,81,106,125,135,158],"proposed":[78,167],"it":[80],"applied":[82],"precise":[84],"fusing":[87],"corrected":[89],"data.":[93],"order":[95],"achieve":[97],"this,":[98],"semantic":[100],"segmentation":[101],"an":[103],"image":[105],"performed":[107],"using":[108,145],"convolutional":[110],"neural":[111],"network,":[112],"mutual":[115,147],"information":[116,148],"between":[117],"measurements":[120],"building":[123],"obtained":[126],"measure":[128],"their":[129],"similarity.":[130],"A":[131],"particle":[132],"filter":[133],"framework":[134],"employed":[136],"localize":[138],"match":[142],"as":[149],"weight":[151],"particle.":[154],"An":[155],"experimental":[156],"dataset":[157],"then":[159],"used":[160],"validate":[162],"feasibility":[164],"method.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
