{"id":"https://openalex.org/W4200142196","doi":"https://doi.org/10.1109/iccais52680.2021.9624576","title":"Real-time Hands-Motion Tracking of Car Driver over Steering-Wheel by Combination of Particle Filter with Deep Neural Network for Body-Region Extraction","display_name":"Real-time Hands-Motion Tracking of Car Driver over Steering-Wheel by Combination of Particle Filter with Deep Neural Network for Body-Region Extraction","publication_year":2021,"publication_date":"2021-10-14","ids":{"openalex":"https://openalex.org/W4200142196","doi":"https://doi.org/10.1109/iccais52680.2021.9624576"},"language":"en","primary_location":{"id":"doi:10.1109/iccais52680.2021.9624576","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais52680.2021.9624576","pdf_url":null,"source":{"id":"https://openalex.org/S4363608071","display_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","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/A5067764774","display_name":"Norikazu Ikoma","orcid":null},"institutions":[{"id":"https://openalex.org/I95053508","display_name":"Nippon Institute of Technology","ror":"https://ror.org/05h68bp56","country_code":"JP","type":"education","lineage":["https://openalex.org/I95053508"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Norikazu Ikoma","raw_affiliation_strings":["Faculty of Fundamental Engineering, Nippon Institute of Technology, Saitama, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Fundamental Engineering, Nippon Institute of Technology, Saitama, Japan","institution_ids":["https://openalex.org/I95053508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5067764774"],"corresponding_institution_ids":["https://openalex.org/I95053508"],"apc_list":null,"apc_paid":null,"fwci":0.9857,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.77701994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"872","last_page":"878"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9965999722480774,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8184518814086914},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.79927659034729},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6701052188873291},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.666522204875946},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6447687149047852},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6423965692520142},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5329713821411133},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.504843533039093},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4138854146003723}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8184518814086914},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.79927659034729},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6701052188873291},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.666522204875946},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6447687149047852},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6423965692520142},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5329713821411133},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.504843533039093},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4138854146003723},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccais52680.2021.9624576","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais52680.2021.9624576","pdf_url":null,"source":{"id":"https://openalex.org/S4363608071","display_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W196852696","https://openalex.org/W1483307070","https://openalex.org/W1782324670","https://openalex.org/W2018160939","https://openalex.org/W2104408738","https://openalex.org/W2121358749","https://openalex.org/W2122462979","https://openalex.org/W2412782625","https://openalex.org/W2630837129","https://openalex.org/W2913518526","https://openalex.org/W6638158750","https://openalex.org/W6678023917"],"related_works":["https://openalex.org/W2015530857","https://openalex.org/W1989212443","https://openalex.org/W2103644279","https://openalex.org/W4302986566","https://openalex.org/W1968585197","https://openalex.org/W2135362996","https://openalex.org/W4247544095","https://openalex.org/W2122155275","https://openalex.org/W2215635302","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"of":[2,27,31,35,57,155],"image":[3,20,42,93],"segmentation":[4,116],"techniques":[5],"based":[6,113,120],"on":[7],"deep":[8,110],"neural":[9,111],"network":[10,112],"provide":[11],"us":[12],"accurate":[13],"body":[14,38,97,115,132],"region":[15,39,98,133],"extraction":[16],"from":[17],"a":[18,80,96,124,160],"camera-captured":[19],"in":[21,65,78,104,148,164],"real-time":[22],"processing":[23],"with":[24,170],"the":[25,36,41,58,91,109,145,149,156,165],"aid":[26],"parallel":[28],"computing":[29],"environment":[30],"GPU.":[32],"Enough":[33],"accuracy":[34],"extracted":[37,131],"over":[40,53,90],"can":[43,138],"be":[44,139],"utilized":[45],"to":[46,86,94,107,144,159],"various":[47],"applications":[48],"including":[49,134],"car-driver's":[50],"hands-motion":[51,59,121],"tracking":[52,60,122],"steering-wheel.":[54],"Conventional":[55],"researches":[56],"have":[61,102],"employed":[62],"color":[63],"cue":[64],"ordinary":[66],"camera,":[67],"which":[68,79],"is":[69,84,99],"strongly":[70],"affected":[71],"by":[72,141],"lighting":[73],"conditions,":[74],"and/or":[75],"depth":[76,82,92],"information,":[77],"special":[81],"sensor":[83],"necessary":[85],"use":[87],"and":[88,136],"post-processing":[89],"extract":[95],"required.":[100],"We":[101],"investigated":[103],"this":[105,129],"paper":[106],"incorporate":[108],"human":[114],"into":[117],"particle":[118,150],"filter":[119,151],"as":[123],"newly":[125],"proposed":[126,157],"method.":[127],"In":[128],"method,":[130],"hands":[135],"arms":[137],"evaluated":[140],"extended":[142],"likelihood":[143],"arm":[146],"direction":[147],"algorithm.":[152],"Real-time":[153],"implementation":[154],"method":[158],"driving":[161],"simulator":[162],"facility":[163],"laboratory":[166],"has":[167],"been":[168],"reported":[169],"some":[171],"experimental":[172],"results.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
