{"id":"https://openalex.org/W3212143793","doi":"https://doi.org/10.1109/icra46639.2022.9812142","title":"Neural Implicit Event Generator for Motion Tracking","display_name":"Neural Implicit Event Generator for Motion Tracking","publication_year":2022,"publication_date":"2022-05-23","ids":{"openalex":"https://openalex.org/W3212143793","doi":"https://doi.org/10.1109/icra46639.2022.9812142","mag":"3212143793"},"language":"en","primary_location":{"id":"doi:10.1109/icra46639.2022.9812142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812142","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","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":"2022 International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5063373009","display_name":"Mana Masuda","orcid":"https://orcid.org/0000-0002-9050-5306"},"institutions":[{"id":"https://openalex.org/I203189479","display_name":"The Open University of Japan","ror":"https://ror.org/03jyr9x65","country_code":"JP","type":"education","lineage":["https://openalex.org/I203189479"]},{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mana Masuda","raw_affiliation_strings":["School of Science for Open and Environmental Systems, Keio University,Tokyo,Japan","School of Science for Open and Environmental Systems, Keio University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science for Open and Environmental Systems, Keio University,Tokyo,Japan","institution_ids":["https://openalex.org/I203189479","https://openalex.org/I203951103"]},{"raw_affiliation_string":"School of Science for Open and Environmental Systems, Keio University, Tokyo, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000254206","display_name":"Yusuke Sekikawa","orcid":"https://orcid.org/0000-0003-1111-5949"},"institutions":[{"id":"https://openalex.org/I4210132650","display_name":"Denso (Japan)","ror":"https://ror.org/04hkpfa76","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210132650"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusuke Sekikawa","raw_affiliation_strings":["Denso IT Laboratory,Tokyo,Japan","Denso IT Laboratory, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Denso IT Laboratory,Tokyo,Japan","institution_ids":["https://openalex.org/I4210132650"]},{"raw_affiliation_string":"Denso IT Laboratory, Tokyo, Japan","institution_ids":["https://openalex.org/I4210132650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076720835","display_name":"Ryo Fujii","orcid":"https://orcid.org/0000-0002-9115-8414"},"institutions":[{"id":"https://openalex.org/I203189479","display_name":"The Open University of Japan","ror":"https://ror.org/03jyr9x65","country_code":"JP","type":"education","lineage":["https://openalex.org/I203189479"]},{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryo Fujii","raw_affiliation_strings":["School of Science for Open and Environmental Systems, Keio University,Tokyo,Japan","School of Science for Open and Environmental Systems, Keio University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science for Open and Environmental Systems, Keio University,Tokyo,Japan","institution_ids":["https://openalex.org/I203189479","https://openalex.org/I203951103"]},{"raw_affiliation_string":"School of Science for Open and Environmental Systems, Keio University, Tokyo, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005819073","display_name":"Hideo Sait\u00f4","orcid":"https://orcid.org/0000-0002-2421-9862"},"institutions":[{"id":"https://openalex.org/I203189479","display_name":"The Open University of Japan","ror":"https://ror.org/03jyr9x65","country_code":"JP","type":"education","lineage":["https://openalex.org/I203189479"]},{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideo Saito","raw_affiliation_strings":["School of Science for Open and Environmental Systems, Keio University,Tokyo,Japan","School of Science for Open and Environmental Systems, Keio University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science for Open and Environmental Systems, Keio University,Tokyo,Japan","institution_ids":["https://openalex.org/I203189479","https://openalex.org/I203951103"]},{"raw_affiliation_string":"School of Science for Open and Environmental Systems, Keio University, Tokyo, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2032,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.86318853,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2200","last_page":"2206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7417675256729126},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.624732255935669},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5540649890899658},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.547530472278595},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.54273521900177},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5212369561195374},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.47054582834243774},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.42273780703544617},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41106516122817993},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3493959307670593},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3062204122543335},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.09111830592155457}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7417675256729126},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.624732255935669},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5540649890899658},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.547530472278595},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.54273521900177},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5212369561195374},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.47054582834243774},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.42273780703544617},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41106516122817993},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3493959307670593},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3062204122543335},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.09111830592155457},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra46639.2022.9812142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra46639.2022.9812142","pdf_url":null,"source":{"id":"https://openalex.org/S4363607759","display_name":"2022 International Conference on Robotics and Automation (ICRA)","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":"2022 International Conference on Robotics and Automation (ICRA)","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":48,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1612997784","https://openalex.org/W1980287119","https://openalex.org/W2016574277","https://openalex.org/W2035379092","https://openalex.org/W2118877769","https://openalex.org/W2470394683","https://openalex.org/W2564632156","https://openalex.org/W2754360834","https://openalex.org/W2766013930","https://openalex.org/W2796402180","https://openalex.org/W2799058067","https://openalex.org/W2884195444","https://openalex.org/W2963926543","https://openalex.org/W2968161291","https://openalex.org/W2969508737","https://openalex.org/W2969945254","https://openalex.org/W2981462813","https://openalex.org/W3000286396","https://openalex.org/W3010268791","https://openalex.org/W3035672751","https://openalex.org/W3046620003","https://openalex.org/W3084220991","https://openalex.org/W3100688879","https://openalex.org/W3102178346","https://openalex.org/W3103648783","https://openalex.org/W3107486934","https://openalex.org/W3109585842","https://openalex.org/W3112108866","https://openalex.org/W3125094233","https://openalex.org/W3127762346","https://openalex.org/W3134123147","https://openalex.org/W3177583232","https://openalex.org/W3204297138","https://openalex.org/W4200150166","https://openalex.org/W4253803843","https://openalex.org/W4287645500","https://openalex.org/W6631190155","https://openalex.org/W6677548441","https://openalex.org/W6720898849","https://openalex.org/W6731149280","https://openalex.org/W6766816269","https://openalex.org/W6772376039","https://openalex.org/W6786033142","https://openalex.org/W6786093842","https://openalex.org/W6789804083","https://openalex.org/W6790664976","https://openalex.org/W6790711872"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W4394861761","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W1925461966","https://openalex.org/W3036468168"],"abstract_inverted_index":{"We":[0,129],"present":[1],"a":[2],"novel":[3],"framework":[4,15,134],"of":[5,82,114,143],"motion":[6,30],"tracking":[7,31,127],"from":[8,50,87],"event":[9,18,24,46,49,89],"data":[10],"using":[11],"implicit":[12,23,77],"expression.":[13],"Our":[14,91],"uses":[16],"pre-trained":[17],"generation":[19],"MLP":[20],"called":[21],"the":[22,41,44,51,61,64,74,80,83,112,124,141],"generator":[25],"(IEG)":[26],"and":[27,37,47,105,145],"carries":[28],"out":[29],"by":[32,60],"updating":[33],"its":[34],"state":[35,53,85],"(position":[36],"velocity)":[38],"based":[39],"on":[40,117],"difference":[42,56],"between":[43],"observed":[45],"generated":[48],"current":[52],"estimation.":[54],"The":[55],"is":[57,94],"computed":[58],"implicitly":[59],"IEG.":[62],"Unlike":[63],"conventional":[65],"explicit":[66],"approach,":[67],"which":[68,102],"requires":[69],"dense":[70],"computation":[71],"to":[72,123],"evaluate":[73],"difference,":[75],"our":[76,115,133],"approach":[78],"realizes":[79],"update":[81],"efficient":[84],"directly":[86],"sparse":[88,92],"data.":[90],"algorithm":[93],"especially":[95],"suitable":[96],"for":[97],"mobile":[98],"robotics":[99],"applications":[100],"in":[101,137,140],"computational":[103],"resources":[104],"battery":[106],"life":[107],"are":[108],"limited.":[109],"To":[110],"verify":[111],"effectiveness":[113],"method":[116],"real-world":[118,138],"data,":[119],"we":[120],"applied":[121],"it":[122],"AR":[125],"marker":[126],"application.":[128],"have":[130],"confirmed":[131],"that":[132],"works":[135],"well":[136],"environments":[139],"presence":[142],"noise":[144],"background":[146],"clutter.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
