{"id":"https://openalex.org/W2163819521","doi":"https://doi.org/10.1109/ivs.2011.5940458","title":"Event-driven track management method for robust multi-vehicle tracking","display_name":"Event-driven track management method for robust multi-vehicle tracking","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2163819521","doi":"https://doi.org/10.1109/ivs.2011.5940458","mag":"2163819521"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2011.5940458","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940458","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","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/A5114255846","display_name":"Young-Chul Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Young-Chul Lim","raw_affiliation_strings":["Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea"],"affiliations":[{"raw_affiliation_string":"Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040459018","display_name":"Chung-Hee Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chung-Hee Lee","raw_affiliation_strings":["Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea"],"affiliations":[{"raw_affiliation_string":"Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110077265","display_name":"Soon Kwon","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soon Kwon","raw_affiliation_strings":["Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea"],"affiliations":[{"raw_affiliation_string":"Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100767723","display_name":"Jonghwan Kim","orcid":"https://orcid.org/0000-0002-9919-9843"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jonghwan Kim","raw_affiliation_strings":["Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea"],"affiliations":[{"raw_affiliation_string":"Division of IT-convergence, Daegu-Gyeongbuk Institute of Science and Technology, South Korea","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114255846"],"corresponding_institution_ids":["https://openalex.org/I193352282"],"apc_list":null,"apc_paid":null,"fwci":1.2879,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.84155975,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9977999925613403,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/track","display_name":"Track (disk drive)","score":0.8162859678268433},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7643229365348816},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5757743716239929},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5636327266693115},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5555303692817688},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5413255095481873},{"id":"https://openalex.org/keywords/vehicle-tracking-system","display_name":"Vehicle tracking system","score":0.49875903129577637},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4164109528064728},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.16293194890022278}],"concepts":[{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.8162859678268433},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7643229365348816},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5757743716239929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5636327266693115},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5555303692817688},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5413255095481873},{"id":"https://openalex.org/C84119951","wikidata":"https://www.wikidata.org/wiki/Q3498530","display_name":"Vehicle tracking system","level":3,"score":0.49875903129577637},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4164109528064728},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.16293194890022278},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2011.5940458","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940458","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1924453835","https://openalex.org/W1985900868","https://openalex.org/W1995129208","https://openalex.org/W2002545408","https://openalex.org/W2094890959","https://openalex.org/W2109168219","https://openalex.org/W2124781496","https://openalex.org/W2139138838","https://openalex.org/W2160671527","https://openalex.org/W2161523654","https://openalex.org/W2163812146","https://openalex.org/W2165949176","https://openalex.org/W2542256560","https://openalex.org/W2543696449","https://openalex.org/W6729025360"],"related_works":["https://openalex.org/W1578117154","https://openalex.org/W2542256560","https://openalex.org/W1543936162","https://openalex.org/W2379485644","https://openalex.org/W3174856089","https://openalex.org/W2167990459","https://openalex.org/W4200050103","https://openalex.org/W2263868195","https://openalex.org/W2836110447","https://openalex.org/W2991130854"],"abstract_inverted_index":{"In":[0,52],"this":[1],"paper,":[2],"we":[3],"present":[4],"an":[5],"event-driven":[6,166],"track":[7,14,70,74,94,120,130,133,167],"management":[8,75,95,168],"method":[9,26,40,76,96,148,169],"to":[10,43,116,123],"detect":[11,28],"reliably":[12],"and":[13,19,49,69,103,143,151,177],"robustly":[15],"while":[16,85],"minimizing":[17],"missing":[18,48],"false":[20,50,63,66,106,175,178],"detections.":[21,51],"No":[22],"state-of-the-art":[23],"vehicle":[24,140],"detection":[25],"can":[27,77],"all":[29],"the":[30,33,45,79,112,165,171,174],"vehicles":[31],"on":[32],"road":[34,158],"without":[35],"error.":[36],"A":[37,119],"multi-vehicle":[38,54],"tracking":[39,55],"is":[41,126,135,149],"essential":[42],"minimize":[44],"number":[46,80,172],"of":[47,61,81,173],"a":[53,129],"method,":[56],"there":[57],"are":[58,109],"three":[59],"types":[60],"errors:":[62],"negative":[64,179],"alarms,":[65,68],"positive":[67,107,176],"identity":[71],"switches.":[72],"Our":[73,93],"reduce":[78],"these":[82],"errors":[83],"remarkably":[84,181],"processing":[86],"in":[87,111,156],"real":[88,157],"time":[89],"for":[90],"online":[91],"application.":[92],"has":[97],"four":[98],"states:":[99],"IDLE,":[100],"PRE-TRACK,":[101],"CUR-TRACK,":[102],"POST-TRACK.":[104],"Most":[105],"alarms":[108,180],"removed":[110],"PRE-TRACK":[113],"state":[114,121],"due":[115],"their":[117],"sparseness.":[118],"transition":[122],"other":[124],"states":[125],"determined":[127],"by":[128,137],"score.":[131],"The":[132,146,160],"score":[134],"calculated":[136],"obstacle":[138],"detection,":[139],"recognition,":[141],"detection-by-tracking,":[142],"data":[144],"association.":[145],"proposed":[147],"tested":[150],"verified":[152],"with":[153,183],"image":[154],"sequences":[155],"environments.":[159],"experimental":[161],"results":[162],"demonstrate":[163],"that":[164],"minimizes":[170],"compared":[182],"previous":[184],"methods.":[185]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}