{"id":"https://openalex.org/W4400648008","doi":"https://doi.org/10.1109/iv55156.2024.10588487","title":"Vision-based hybrid object tracking for autonomous vehicles","display_name":"Vision-based hybrid object tracking for autonomous vehicles","publication_year":2024,"publication_date":"2024-06-02","ids":{"openalex":"https://openalex.org/W4400648008","doi":"https://doi.org/10.1109/iv55156.2024.10588487"},"language":"en","primary_location":{"id":"doi:10.1109/iv55156.2024.10588487","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv55156.2024.10588487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5048934265","display_name":"Hsiu\u2010Min Chuang","orcid":"https://orcid.org/0000-0002-1646-5190"},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hsiu-Min Chuang","raw_affiliation_strings":["Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238"],"affiliations":[{"raw_affiliation_string":"Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110481239","display_name":"Masamitsu Tsuchiya","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masamitsu Tsuchiya","raw_affiliation_strings":["Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238"],"affiliations":[{"raw_affiliation_string":"Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052852409","display_name":"Satoru Araki","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoru Araki","raw_affiliation_strings":["Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238"],"affiliations":[{"raw_affiliation_string":"Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021392103","display_name":"Riku Inoue","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Riku Inoue","raw_affiliation_strings":["Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238"],"affiliations":[{"raw_affiliation_string":"Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049116554","display_name":"Tokitomo Ariyoshi","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tokitomo Ariyoshi","raw_affiliation_strings":["Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238"],"affiliations":[{"raw_affiliation_string":"Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238","institution_ids":["https://openalex.org/I1283473643"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109523475","display_name":"Yuji Yasui","orcid":null},"institutions":[{"id":"https://openalex.org/I1283473643","display_name":"Honda (Japan)","ror":"https://ror.org/03jzay846","country_code":"JP","type":"company","lineage":["https://openalex.org/I1283473643"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuji Yasui","raw_affiliation_strings":["Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238"],"affiliations":[{"raw_affiliation_string":"Honda R&D Co., Ltd.,Innovative Research Excellence,Tokyo,Japan,107-6238","institution_ids":["https://openalex.org/I1283473643"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5048934265"],"corresponding_institution_ids":["https://openalex.org/I1283473643"],"apc_list":null,"apc_paid":null,"fwci":0.222,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50590961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"10","issue":null,"first_page":"722","last_page":"729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.8792999982833862,"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"}},"topics":[{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.8792999982833862,"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"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.8697999715805054,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.8427000045776367,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7288210391998291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6611735820770264},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6450021862983704},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5114004015922546},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5020327568054199},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.47161439061164856},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4105573296546936},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.07961133122444153}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7288210391998291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6611735820770264},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6450021862983704},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5114004015922546},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5020327568054199},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.47161439061164856},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4105573296546936},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.07961133122444153},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55156.2024.10588487","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iv55156.2024.10588487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1985925619","https://openalex.org/W2222512263","https://openalex.org/W2560544142","https://openalex.org/W2771373885","https://openalex.org/W2798462325","https://openalex.org/W2951517617","https://openalex.org/W2963400571","https://openalex.org/W2964166085","https://openalex.org/W3004351857","https://openalex.org/W3017930107","https://openalex.org/W3034681945","https://openalex.org/W3035346742","https://openalex.org/W3107819843","https://openalex.org/W3117804044","https://openalex.org/W3176287975","https://openalex.org/W3190752170","https://openalex.org/W3208826636","https://openalex.org/W4205547213","https://openalex.org/W4211154833","https://openalex.org/W4231465875","https://openalex.org/W4242650066","https://openalex.org/W4320002812","https://openalex.org/W6803118227"],"related_works":["https://openalex.org/W4389065903","https://openalex.org/W2158788032","https://openalex.org/W2385949326","https://openalex.org/W1966005655","https://openalex.org/W3135795035","https://openalex.org/W2789220062","https://openalex.org/W2811496562","https://openalex.org/W2094665863","https://openalex.org/W2071984725","https://openalex.org/W2185534064"],"abstract_inverted_index":{"Vision-based":[0],"object":[1,37,108],"detection":[2,38,170],"and":[3,24,39,124,147,183],"tracking":[4,40,109],"play":[5],"a":[6,104,119,125],"critical":[7],"role":[8],"in":[9,67],"the":[10,18,31,51,62,77,138,148,193,200],"field":[11],"of":[12,34,65,87,171,195],"autonomous":[13,52],"driving":[14,53],"as":[15,61],"they":[16],"enable":[17],"ego-car":[19,177],"to":[20,44,55,58,79,93,134,198],"identify":[21],"potential":[22],"dangers":[23,82],"detect":[25,135],"objects":[26,66],"that":[27,160],"emerge":[28],"suddenly.":[29],"However,":[30],"current":[32],"frequency":[33],"out-of-state":[35],"vision-based":[36,106],"perception":[41,117,121,127,165],"is":[42,48],"limited":[43],"approximately":[45],"10-20Hz,":[46],"which":[47],"insufficient":[49],"for":[50],"system":[54,122,128],"promptly":[56,80],"respond":[57],"events":[59],"such":[60],"sudden":[63],"appearance":[64],"close":[68],"proximity":[69],"or":[70],"high-speed":[71],"scenarios.":[72],"In":[73],"contrast,":[74],"animals":[75],"possess":[76],"ability":[78],"avoid":[81],"despite":[83],"lacking":[84],"precise":[85],"knowledge":[86],"an":[88],"object\u2019s":[89,201],"exact":[90],"distance,":[91],"owing":[92],"their":[94],"eyes\u2019":[95],"high":[96],"flicker":[97],"fusion":[98],"rates.":[99,156],"Consequently,":[100],"this":[101],"paper":[102],"introduces":[103],"novel":[105],"hybrid":[107],"technique.":[110],"The":[111],"proposed":[112,189],"approach":[113],"incorporates":[114],"two":[115],"distinct":[116],"systems:":[118],"multi-camera":[120],"(MCP)":[123],"high-frequency":[126],"(HFP).":[129],"These":[130],"systems":[131,197],"operate":[132],"independently":[133],"objects,":[136],"with":[137],"MCP":[139,182],"offering":[140],"higher":[141,154],"accuracy":[142,152],"albeit":[143],"lower":[144,151],"update":[145,155],"rates,":[146],"HFP":[149,184],"providing":[150],"but":[153],"Experimental":[157],"results":[158],"demonstrate":[159],"our":[161,188],"method":[162,190],"surpasses":[163],"traditional":[164],"approaches":[166],"by":[167],"achieving":[168],"faster":[169],"real-time":[172],"pop-out":[173],"motorbikes":[174],"across":[175],"various":[176],"speeds.":[178],"Moreover,":[179],"when":[180],"both":[181,196],"information":[185],"are":[186],"available,":[187],"effectively":[191],"combines":[192],"strengths":[194],"estimate":[199],"status.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}