{"id":"https://openalex.org/W2774832664","doi":"https://doi.org/10.1109/mfi.2017.8170434","title":"Occlusion handling and track management method of high-level sensor fusion for robust pedestrian tracking","display_name":"Occlusion handling and track management method of high-level sensor fusion for robust pedestrian tracking","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2774832664","doi":"https://doi.org/10.1109/mfi.2017.8170434","mag":"2774832664"},"language":"en","primary_location":{"id":"doi:10.1109/mfi.2017.8170434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2017.8170434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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/A5079351110","display_name":"Seong-Geun Shin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095514","display_name":"Korea Automotive Technology Institute","ror":"https://ror.org/00sc3t321","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210095514"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Geun Shin","raw_affiliation_strings":["Division of Smart Car Technology R&D, Korea Automotive Technology Institute(KATech), Chungnam, Republic of"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Smart Car Technology R&D, Korea Automotive Technology Institute(KATech), Chungnam, Republic of","institution_ids":["https://openalex.org/I4210095514"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075903383","display_name":"Dae-ryong Ahn","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095514","display_name":"Korea Automotive Technology Institute","ror":"https://ror.org/00sc3t321","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210095514"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dae-Ryong Ahn","raw_affiliation_strings":["Division of Smart Car Technology R&D, Korea Automotive Technology Institute(KATech), Chungnam, Republic of"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Smart Car Technology R&D, Korea Automotive Technology Institute(KATech), Chungnam, Republic of","institution_ids":["https://openalex.org/I4210095514"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068673676","display_name":"Hyuck-Kee Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095514","display_name":"Korea Automotive Technology Institute","ror":"https://ror.org/00sc3t321","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210095514"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyuck-Kee Lee","raw_affiliation_strings":["Division of Smart Car Technology R&D, Korea Automotive Technology Institute(KATech), Chungnam, Republic of"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Smart Car Technology R&D, Korea Automotive Technology Institute(KATech), Chungnam, Republic of","institution_ids":["https://openalex.org/I4210095514"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2771,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.65994154,"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":"233","last_page":"238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958000183105469,"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":0.9958000183105469,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9704999923706055,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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-vision","display_name":"Computer vision","score":0.7555191516876221},{"id":"https://openalex.org/keywords/occlusion","display_name":"Occlusion","score":0.7103884220123291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7048627138137817},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.7024104595184326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6536819934844971},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6304082870483398},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.5401579141616821},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4591732323169708},{"id":"https://openalex.org/keywords/tracking-system","display_name":"Tracking system","score":0.44069725275039673},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.440077006816864},{"id":"https://openalex.org/keywords/field-of-view","display_name":"Field of view","score":0.4241946339607239},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.41530823707580566},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.2514423131942749},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.10812190175056458}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7555191516876221},{"id":"https://openalex.org/C2776268601","wikidata":"https://www.wikidata.org/wiki/Q968808","display_name":"Occlusion","level":2,"score":0.7103884220123291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7048627138137817},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.7024104595184326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6536819934844971},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6304082870483398},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.5401579141616821},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4591732323169708},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.44069725275039673},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.440077006816864},{"id":"https://openalex.org/C150627866","wikidata":"https://www.wikidata.org/wiki/Q1076893","display_name":"Field of view","level":2,"score":0.4241946339607239},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.41530823707580566},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2514423131942749},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.10812190175056458},{"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi.2017.8170434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi.2017.8170434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1947516467","https://openalex.org/W2080718434","https://openalex.org/W2107088745","https://openalex.org/W2127707627","https://openalex.org/W2145299066","https://openalex.org/W2155680787","https://openalex.org/W2157468226","https://openalex.org/W2163819521","https://openalex.org/W2183873254","https://openalex.org/W2424637586","https://openalex.org/W2507230881","https://openalex.org/W3144574585","https://openalex.org/W6717797309"],"related_works":["https://openalex.org/W2318603563","https://openalex.org/W887692824","https://openalex.org/W2354419434","https://openalex.org/W2021121433","https://openalex.org/W4285271403","https://openalex.org/W3178626677","https://openalex.org/W2110357291","https://openalex.org/W3015801620","https://openalex.org/W2408440673","https://openalex.org/W2091015105"],"abstract_inverted_index":{"In":[0,18],"object":[1],"tracking":[2,16,29,35],"field,":[3],"occlusion":[4,50,83,108,117,139,153],"situations":[5],"between":[6,40,52,141,155],"objects":[7,54],"are":[8],"important":[9],"factors":[10],"that":[11],"degrade":[12],"the":[13,28,33,49,57,91,99,107,111,114,122,129,138,148,152],"performance":[14,150],"of":[15,59,98,110,116,128],"algorithms.":[17],"this":[19],"paper,":[20],"we":[21],"present":[22],"a":[23,69,75,78],"track":[24,103,112],"management":[25,104],"method":[26],"in":[27,68,137,151],"level":[30],"to":[31,65],"solve":[32],"discontinuous":[34],"problem":[36],"caused":[37],"by":[38,47,87],"occlusions":[39],"detected":[41,53,100],"objects.":[42,101],"This":[43],"work":[44],"is":[45,85],"performed":[46],"predicting":[48],"situation":[51,140,154],"and":[55,77,95,126,143],"managing":[56],"state":[58,109],"tracks":[60],"based":[61],"on":[62],"an":[63],"approach":[64,73,133],"track-to-track":[66],"fusion":[67,72],"high-level":[70],"sensor":[71],"using":[74],"lidar":[76],"monocular":[79],"camera":[80],"sensor.":[81],"The":[82,102,131],"prediction":[84,118],"computed":[86],"taking":[88],"into":[89],"account":[90],"width,":[92],"length,":[93],"position":[94],"azimuth":[96],"angle":[97],"system":[105],"manages":[106],"from":[113],"result":[115],"as":[119,121],"well":[120],"initialization,":[123],"creation,":[124],"confirmation":[125],"deletion":[127],"tracks.":[130],"proposed":[132],"has":[134],"been":[135],"verified":[136],"pedestrians,":[142],"our":[144],"experimental":[145],"results":[146],"showed":[147],"intended":[149],"pedestrians.":[156]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}