{"id":"https://openalex.org/W4214620022","doi":"https://doi.org/10.1109/imcom53663.2022.9721744","title":"Person Identification Based on Accelerations on Drawing Figures with a Smartphone","display_name":"Person Identification Based on Accelerations on Drawing Figures with a Smartphone","publication_year":2022,"publication_date":"2022-01-03","ids":{"openalex":"https://openalex.org/W4214620022","doi":"https://doi.org/10.1109/imcom53663.2022.9721744"},"language":"en","primary_location":{"id":"doi:10.1109/imcom53663.2022.9721744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/imcom53663.2022.9721744","pdf_url":null,"source":{"id":"https://openalex.org/S4363608555","display_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","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 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","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/A5101151887","display_name":"Yoshihaya Takahashi","orcid":null},"institutions":[{"id":"https://openalex.org/I116465919","display_name":"Kogakuin University","ror":"https://ror.org/01wc2tq75","country_code":"JP","type":"education","lineage":["https://openalex.org/I116465919"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshihaya Takahashi","raw_affiliation_strings":["Kogakuin University Graduate School,Electrical Engineering and Electronics,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kogakuin University Graduate School,Electrical Engineering and Electronics,Tokyo,Japan","institution_ids":["https://openalex.org/I116465919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046363409","display_name":"Atsuya Sonoyama","orcid":null},"institutions":[{"id":"https://openalex.org/I116465919","display_name":"Kogakuin University","ror":"https://ror.org/01wc2tq75","country_code":"JP","type":"education","lineage":["https://openalex.org/I116465919"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsuya Sonoyama","raw_affiliation_strings":["Kogakuin University Graduate School,Electrical Engineering and Electronics,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kogakuin University Graduate School,Electrical Engineering and Electronics,Tokyo,Japan","institution_ids":["https://openalex.org/I116465919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090205270","display_name":"Takeshi Kamiyamaton","orcid":null},"institutions":[{"id":"https://openalex.org/I43777268","display_name":"Nagasaki University","ror":"https://ror.org/058h74p94","country_code":"JP","type":"education","lineage":["https://openalex.org/I43777268"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeshi Kamiyamaton","raw_affiliation_strings":["Nagasaki University,School of Information and Data Sciences,Nagasaki,Japan","School of Information and Data Sciences, Nagasaki University, Nagasaki, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nagasaki University,School of Information and Data Sciences,Nagasaki,Japan","institution_ids":["https://openalex.org/I43777268"]},{"raw_affiliation_string":"School of Information and Data Sciences, Nagasaki University, Nagasaki, Japan","institution_ids":["https://openalex.org/I43777268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026650274","display_name":"Masato Oguchi","orcid":null},"institutions":[{"id":"https://openalex.org/I26120043","display_name":"Ochanomizu University","ror":"https://ror.org/03599d813","country_code":"JP","type":"education","lineage":["https://openalex.org/I26120043"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masato Oguchi","raw_affiliation_strings":["Ochanomizu University,Department of Information Sciences,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ochanomizu University,Department of Information Sciences,Tokyo,Japan","institution_ids":["https://openalex.org/I26120043"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041517596","display_name":"Saneyasu Yamaguchi","orcid":"https://orcid.org/0000-0002-1385-7922"},"institutions":[{"id":"https://openalex.org/I116465919","display_name":"Kogakuin University","ror":"https://ror.org/01wc2tq75","country_code":"JP","type":"education","lineage":["https://openalex.org/I116465919"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Saneyasu Yamaguchi","raw_affiliation_strings":["Kogakuin University,Department of Information and Communications Engineering,Tokyo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kogakuin University,Department of Information and Communications Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I116465919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01230334,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9983999729156494,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9983999729156494,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996999979019165,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.8623557090759277},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.827627420425415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8129082322120667},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.7258037328720093},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49947524070739746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.490375280380249},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47339141368865967},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.38958442211151123},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3756125271320343},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.34827643632888794}],"concepts":[{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.8623557090759277},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.827627420425415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8129082322120667},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.7258037328720093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49947524070739746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.490375280380249},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47339141368865967},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.38958442211151123},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3756125271320343},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.34827643632888794},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/imcom53663.2022.9721744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/imcom53663.2022.9721744","pdf_url":null,"source":{"id":"https://openalex.org/S4363608555","display_name":"2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","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 16th International Conference on Ubiquitous Information Management and Communication (IMCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2270470215","https://openalex.org/W2750664618","https://openalex.org/W2915815650","https://openalex.org/W2971432638","https://openalex.org/W2971553856","https://openalex.org/W3014941347","https://openalex.org/W3106663407","https://openalex.org/W3122806818","https://openalex.org/W3205480107"],"related_works":["https://openalex.org/W2765080098","https://openalex.org/W2385749422","https://openalex.org/W2355290145","https://openalex.org/W2353465659","https://openalex.org/W2009888974","https://openalex.org/W2355539379","https://openalex.org/W4384517610","https://openalex.org/W4288389100","https://openalex.org/W1902800522","https://openalex.org/W2339469482"],"abstract_inverted_index":{"Several":[0],"methods":[1,28],"to":[2,42,74,126],"estimate":[3],"the":[4,13,17,37,40,55,58,86,94,144,149,155,167,172,179,182],"user":[5,41,59,77,81,98,145,173],"who":[6,146],"is":[7,91,99,111,117,147,151,186],"holding":[8,148],"a":[9,44,47,65,72,76,80,83,97,128],"smartphone":[10,45,150],"by":[11,78,119],"analyzing":[12],"acceleration":[14,62,124,133],"obtained":[15],"from":[16,101],"smartphone's":[18],"accelerometer":[19],"using":[20,122,140,158,184],"deep":[21,120],"learning":[22,116,121],"have":[23,29],"been":[24],"proposed.":[25],"However,":[26],"these":[27,123],"some":[30],"issues":[31],"such":[32],"as":[33],"insufficient":[34],"accuracy":[35,180],"or":[36],"need":[38],"for":[39,46,130,136],"hold":[43],"long":[48],"time.":[49,69],"In":[50,177],"this":[51,141],"paper,":[52],"we":[53],"discuss":[54],"estimation":[56],"of":[57,68,108,181],"based":[60,92],"on":[61,93],"measured":[63,135],"in":[64,85,104,113],"shorter":[66],"aperiod":[67],"We":[70,153],"propose":[71],"method":[73,90,157,169,183],"identify":[75,171],"make":[79],"draw":[82],"figure":[84],"air.":[87],"The":[88,132],"proposed":[89,156,168],"assumption":[95],"that":[96,166],"estimated":[100],"users":[102,110],"given":[103],"advance.":[105],"Acceleration":[106],"data":[107,125,134],"all":[109],"acquired":[112],"advance,":[114],"and":[115,143,162,164],"performed":[118],"create":[127],"model":[129],"estimation.":[131],"identification":[137],"are":[138],"analyzed":[139],"model,":[142],"idenfitied.":[152],"evaluated":[154],"two":[159],"networks,":[160],"LSTM":[161],"DeepConvLSTM,":[163],"showed":[165],"can":[170],"with":[174],"high":[175],"accuracy.":[176],"particular,":[178],"DeepConvLSTM":[185],"high.":[187]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
