{"id":"https://openalex.org/W4391768405","doi":"https://doi.org/10.1109/itsc57777.2023.10422478","title":"ArUco-based Automatic Extrinsic Sensor Calibration for Driverless Train System*","display_name":"ArUco-based Automatic Extrinsic Sensor Calibration for Driverless Train System*","publication_year":2023,"publication_date":"2023-09-24","ids":{"openalex":"https://openalex.org/W4391768405","doi":"https://doi.org/10.1109/itsc57777.2023.10422478"},"language":"en","primary_location":{"id":"doi:10.1109/itsc57777.2023.10422478","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/itsc57777.2023.10422478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","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/A5019645361","display_name":"Sudhir Kumar Pandey","orcid":"https://orcid.org/0000-0003-3807-9423"},"institutions":[{"id":"https://openalex.org/I65143321","display_name":"Hitachi (Japan)","ror":"https://ror.org/02exqgm79","country_code":"JP","type":"company","lineage":["https://openalex.org/I65143321"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Jyotsna Pandey","raw_affiliation_strings":["Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292"],"affiliations":[{"raw_affiliation_string":"Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292","institution_ids":["https://openalex.org/I65143321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077219702","display_name":"Takumi Kudo","orcid":"https://orcid.org/0000-0002-0938-7593"},"institutions":[{"id":"https://openalex.org/I65143321","display_name":"Hitachi (Japan)","ror":"https://ror.org/02exqgm79","country_code":"JP","type":"company","lineage":["https://openalex.org/I65143321"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kudo Takumi","raw_affiliation_strings":["Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292"],"affiliations":[{"raw_affiliation_string":"Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292","institution_ids":["https://openalex.org/I65143321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093917589","display_name":"Shimizu Taku","orcid":null},"institutions":[{"id":"https://openalex.org/I65143321","display_name":"Hitachi (Japan)","ror":"https://ror.org/02exqgm79","country_code":"JP","type":"company","lineage":["https://openalex.org/I65143321"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shimizu Taku","raw_affiliation_strings":["Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292"],"affiliations":[{"raw_affiliation_string":"Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292","institution_ids":["https://openalex.org/I65143321"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045823168","display_name":"Kenji Imamoto","orcid":null},"institutions":[{"id":"https://openalex.org/I65143321","display_name":"Hitachi (Japan)","ror":"https://ror.org/02exqgm79","country_code":"JP","type":"company","lineage":["https://openalex.org/I65143321"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Imamoto Kenji","raw_affiliation_strings":["Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292"],"affiliations":[{"raw_affiliation_string":"Hitachi Research Laboratory,Ibaraki,JAPAN,319\u20131292","institution_ids":["https://openalex.org/I65143321"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019645361"],"corresponding_institution_ids":["https://openalex.org/I65143321"],"apc_list":null,"apc_paid":null,"fwci":0.2024,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56098412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"4303","last_page":"4308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9580000042915344,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9580000042915344,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9061999917030334,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7091770768165588},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6739652156829834},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0783149003982544}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7091770768165588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6739652156829834},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0783149003982544},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc57777.2023.10422478","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/itsc57777.2023.10422478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.6700000166893005,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1994349244","https://openalex.org/W2014043297","https://openalex.org/W2103893524","https://openalex.org/W2133505209","https://openalex.org/W2145023731","https://openalex.org/W2980040548","https://openalex.org/W3143504974","https://openalex.org/W4220808978","https://openalex.org/W4221152040","https://openalex.org/W4226214856","https://openalex.org/W4309913730","https://openalex.org/W4403179363"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655"],"abstract_inverted_index":{"To":[0,16],"realize":[1],"driverless":[2],"operation":[3],"of":[4,28,41,115,118],"railways":[5],"on":[6],"general":[7],"lines,":[8],"highly":[9],"reliable":[10],"forward":[11],"monitoring":[12],"devices":[13],"are":[14,83],"required.":[15,48],"ensure":[17],"high":[18],"reliability,":[19],"a":[20,52,86,98,122],"sensor":[21,43,57,107],"fusion":[22],"that":[23],"integrates":[24],"the":[25,62,103,110,113,116],"detection":[26],"results":[27],"multiple":[29],"sensors":[30],"is":[31,47,75,135],"used,":[32],"but":[33],"in":[34],"order":[35],"to":[36,60],"integrate":[37],"properly,":[38],"strict":[39],"calibration":[40,58,87],"each":[42],"position":[44],"and":[45,68,105],"posture":[46],"In":[49],"this":[50],"research,":[51],"target":[53],"based":[54],"automatic":[55],"extrinsic":[56],"algorithm":[59],"obtain":[61],"relative":[63],"pose":[64],"transformation":[65],"between":[66,112],"camera":[67,104],"3D":[69],"Light":[70],"Detection":[71],"And":[72],"Ranging":[73],"(LiDAR)":[74],"proposed.":[76],"The":[77,89],"fiducial":[78],"marker":[79,93],"called":[80],"\u2018ArUco\u2019":[81],"markers":[82],"used":[84],"as":[85,97],"target.":[88],"method":[90,125,131],"employs":[91],"ArUco":[92],"feature":[94],"points":[95],"(corners":[96],"feature)":[99],"extraction":[100],"simultaneously":[101],"by":[102],"LiDAR":[106],"data.":[108],"Determining":[109],"relationship":[111],"coordinates":[114],"features":[117],"two":[119],"data":[120],"sets,":[121],"least":[123],"square":[124],"with":[126],"Single":[127],"Value":[128],"Decomposition":[129],"(SVD)":[130],"for":[132],"matrix":[133],"formulation":[134],"utilized.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
