{"id":"https://openalex.org/W4390750671","doi":"https://doi.org/10.1109/tim.2024.3351227","title":"Deep Domain Generalization-Based Indoor Pedestrian Identification Using Footstep-Induced Vibrations","display_name":"Deep Domain Generalization-Based Indoor Pedestrian Identification Using Footstep-Induced Vibrations","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4390750671","doi":"https://doi.org/10.1109/tim.2024.3351227"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2024.3351227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3351227","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5101520289","display_name":"Xuebing Xu","orcid":"https://orcid.org/0000-0002-3109-499X"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuebing Xu","raw_affiliation_strings":["School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-3109-499X","affiliations":[{"raw_affiliation_string":"School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093675557","display_name":"Ruipeng Deng","orcid":"https://orcid.org/0009-0005-0684-6538"},"institutions":[{"id":"https://openalex.org/I173288447","display_name":"Grinnell College","ror":"https://ror.org/04tmmky42","country_code":"US","type":"education","lineage":["https://openalex.org/I173288447"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruipeng Deng","raw_affiliation_strings":["Mathematics Department, Grinnell College, Grinnell, IA, USA"],"raw_orcid":"https://orcid.org/0009-0005-0684-6538","affiliations":[{"raw_affiliation_string":"Mathematics Department, Grinnell College, Grinnell, IA, USA","institution_ids":["https://openalex.org/I173288447"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013421562","display_name":"Guilong Zhao","orcid":"https://orcid.org/0009-0000-3256-428X"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gerui Zhao","raw_affiliation_strings":["School of Information and Communication Engineering, Communication University of China, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-3256-428X","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078041957","display_name":"B.L. Zhang","orcid":"https://orcid.org/0000-0003-1148-9262"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Zhang","raw_affiliation_strings":["Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, USA"],"raw_orcid":"https://orcid.org/0000-0003-1148-9262","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, USA","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384344","display_name":"Cheng Liu","orcid":"https://orcid.org/0000-0003-4174-2046"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cheng Liu","raw_affiliation_strings":["Department of Mechanical Engineering, Stanford University, Stanford, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4174-2046","affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101520289"],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":0.707,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.64059853,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9973999857902527,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/discriminative-model","display_name":"Discriminative model","score":0.7587798833847046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7140529155731201},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6637134552001953},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6146273612976074},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4703688323497772},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43356990814208984},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.4249017834663391},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42435282468795776},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.42240458726882935},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42152485251426697},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.35807815194129944},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3450397849082947},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21405217051506042}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7587798833847046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7140529155731201},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6637134552001953},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6146273612976074},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4703688323497772},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43356990814208984},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.4249017834663391},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42435282468795776},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.42240458726882935},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42152485251426697},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.35807815194129944},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3450397849082947},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21405217051506042},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2024.3351227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3351227","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2756053574","https://openalex.org/W2778644572","https://openalex.org/W2927117501","https://openalex.org/W2963043696","https://openalex.org/W2977117446","https://openalex.org/W2981599901","https://openalex.org/W2991497298","https://openalex.org/W2995669151","https://openalex.org/W3083484445","https://openalex.org/W3084419470","https://openalex.org/W3111021054","https://openalex.org/W3112628962","https://openalex.org/W3114061936","https://openalex.org/W3117302848","https://openalex.org/W3136905523","https://openalex.org/W3174621004","https://openalex.org/W3215849178","https://openalex.org/W4205984557","https://openalex.org/W4310678772","https://openalex.org/W4310880230","https://openalex.org/W4315475304","https://openalex.org/W4320169056","https://openalex.org/W4360977240","https://openalex.org/W4393820119","https://openalex.org/W4393829224","https://openalex.org/W6771271773","https://openalex.org/W6774630179","https://openalex.org/W6782948914","https://openalex.org/W6804272216","https://openalex.org/W6862704348"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2392100589","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2751005898","https://openalex.org/W1487808658"],"abstract_inverted_index":{"Pedestrian":[0],"identification":[1,9,27,162],"based":[2],"on":[3,73],"footstep-induced":[4],"vibrations":[5],"is":[6,32,55,92],"a":[7,42,80,95,107],"nonintrusive":[8],"method":[10,46],"requiring":[11],"sparse":[12],"sensor":[13],"layout":[14],"for":[15,88,131],"biometrics":[16],"in":[17,23,76,106,134],"smart":[18],"buildings.":[19],"Affected":[20],"by":[21],"variations":[22],"environments,":[24],"developing":[25],"pedestrian":[26,161],"algorithms":[28],"across":[29,168],"different":[30],"scenarios":[31],"challenging.":[33],"To":[34],"enhance":[35],"the":[36,58,74,120,132,135,144,151,155],"reusability":[37],"and":[38,52,110,123],"transferability":[39],"of":[40,143,154],"identification,":[41],"deep":[43,53,81],"domain":[44,49,109,129],"generalization-based":[45],"combining":[47],"time-frequency":[48,64],"signal":[50],"processing":[51],"learning":[54],"proposed.":[56],"First,":[57],"collected":[59],"signals":[60],"are":[61,117],"converted":[62],"into":[63],"images":[65],"through":[66,114],"continuous":[67],"wavelet":[68],"transform":[69],"(CWT)":[70],"to":[71,98,127],"focus":[72],"changes":[75],"energy":[77],"distribution.":[78],"Second,":[79],"residual":[82],"shrinkage":[83],"network":[84,97],"(DRSN)":[85],"specially":[86],"designed":[87],"noise":[89],"component":[90],"suppression":[91],"used":[93],"as":[94,119],"backbone":[96],"automatically":[99],"extract":[100],"features.":[101],"Third,":[102],"classification":[103],"information":[104],"inherently":[105],"single":[108],"discriminative":[111],"knowledge":[112],"generated":[113],"multiple":[115,147],"domains":[116],"learned":[118],"internally":[121],"invariant":[122,125],"mutually":[124],"features":[126],"provide":[128],"invariance":[130],"classifier":[133],"domain-invariant":[136],"feature":[137],"exploration":[138],"(DIFEX)":[139],"model.":[140],"The":[141],"results":[142],"experiments":[145],"involving":[146],"influencing":[148],"factors":[149],"demonstrated":[150],"great":[152],"generalization":[153],"proposed":[156],"method,":[157],"which":[158],"achieves":[159],"consistent":[160],"performance":[163],"with":[164],"over":[165],"90%":[166],"accuracy":[167],"various":[169],"environments.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
