{"id":"https://openalex.org/W7154036133","doi":"https://doi.org/10.1145/3772318.3790623","title":"FlowGait: Enabling Robust Long-Term Gait Recognition Across Real-World Covariates with mmWave Radar","display_name":"FlowGait: Enabling Robust Long-Term Gait Recognition Across Real-World Covariates with mmWave Radar","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W7154036133","doi":"https://doi.org/10.1145/3772318.3790623"},"language":null,"primary_location":{"id":"doi:10.1145/3772318.3790623","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772318.3790623","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3772318.3790623","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Dequan Wang","orcid":"https://orcid.org/0000-0003-0877-4636"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dequan Wang","raw_affiliation_strings":["University of Science and Technology of China, HeFei, China"],"raw_orcid":"https://orcid.org/0000-0003-0877-4636","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, HeFei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101989063","display_name":"Chenming He","orcid":"https://orcid.org/0009-0008-2330-3799"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenming He","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0008-2330-3799","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lingyu Wang","orcid":"https://orcid.org/0009-0005-5524-1025"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyu Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0005-5524-1025","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023863179","display_name":"Chengzhen Meng","orcid":"https://orcid.org/0009-0006-4285-1905"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengzhen Meng","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0006-4285-1905","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaoran Fan","orcid":"https://orcid.org/0009-0002-1589-4222"},"institutions":[{"id":"https://openalex.org/I4210121988","display_name":"Film Independent","ror":"https://ror.org/036cy3843","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210121988"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoran Fan","raw_affiliation_strings":["Independent Researcher, Sunnyvale, California, USA"],"raw_orcid":"https://orcid.org/0009-0002-1589-4222","affiliations":[{"raw_affiliation_string":"Independent Researcher, Sunnyvale, California, USA","institution_ids":["https://openalex.org/I4210121988"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103041851","display_name":"Yanyong Zhang","orcid":"https://orcid.org/0000-0001-9046-798X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyong Zhang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-9046-798X","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50456035,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9469000101089478,"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":0.9469000101089478,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.015799999237060547,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.008500000461935997,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7343000173568726},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.5424000024795532},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.5011000037193298},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.47780001163482666},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.4108999967575073},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.39309999346733093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37130001187324524},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3571999967098236}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7343000173568726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6938999891281128},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.589900016784668},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.5424000024795532},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.5011000037193298},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.47780001163482666},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3783999979496002},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3409999907016754},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.33160001039505005},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3231000006198883},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28679999709129333},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2824000120162964},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.25279998779296875},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3772318.3790623","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772318.3790623","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3772318.3790623","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772318.3790623","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1965306520","https://openalex.org/W1975424657","https://openalex.org/W2095416182","https://openalex.org/W2110999135","https://openalex.org/W2120116058","https://openalex.org/W2153654241","https://openalex.org/W2156131785","https://openalex.org/W2414372972","https://openalex.org/W2517331439","https://openalex.org/W2590598362","https://openalex.org/W2798205579","https://openalex.org/W2804268810","https://openalex.org/W2896542121","https://openalex.org/W2907300063","https://openalex.org/W2972637407","https://openalex.org/W2972657490","https://openalex.org/W2979411809","https://openalex.org/W2997616834","https://openalex.org/W3008732063","https://openalex.org/W3009059746","https://openalex.org/W3035040255","https://openalex.org/W3035400973","https://openalex.org/W3046956326","https://openalex.org/W3134310801","https://openalex.org/W3159497806","https://openalex.org/W3195852174","https://openalex.org/W3201939655","https://openalex.org/W3202142426","https://openalex.org/W4214612132","https://openalex.org/W4224925153","https://openalex.org/W4287251614","https://openalex.org/W4294891410","https://openalex.org/W4294891853","https://openalex.org/W4306178647","https://openalex.org/W4312320062","https://openalex.org/W4372266016","https://openalex.org/W4385780761","https://openalex.org/W4387087042","https://openalex.org/W4388116817","https://openalex.org/W4392823854","https://openalex.org/W4393159850","https://openalex.org/W4396955496","https://openalex.org/W4402349737","https://openalex.org/W4402349817","https://openalex.org/W4402349936","https://openalex.org/W4402660067","https://openalex.org/W4403791957","https://openalex.org/W4404056729","https://openalex.org/W4405014543","https://openalex.org/W4407354655","https://openalex.org/W4414173893","https://openalex.org/W4416926492"],"related_works":[],"abstract_inverted_index":{"Gait":[0],"recognition":[1],"enables":[2],"proactive":[3],"and":[4,25,85,118,130],"personalized":[5],"smart":[6],"home":[7],"interactions,":[8],"but":[9],"its":[10,148],"long-term":[11,49,136],"reliability":[12],"is":[13],"challenged":[14],"by":[15,68],"the":[16,58,93,101,135],"non-static":[17],"nature":[18,96],"of":[19,125],"gait.":[20],"Covariates":[21],"like":[22],"carrying":[23],"items":[24],"clothing":[26],"induce":[27],"a":[28,43,64,77,86],"persistent":[29],"domain":[30],"shift":[31],"that":[32,91],"degrades":[33],"traditional,":[34],"static":[35],"models.":[36],"To":[37],"solve":[38],"this,":[39],"we":[40],"introduce":[41],"FlowGait,":[42],"mmWave-based":[44],"framework":[45],"designed":[46],"for":[47,81,134],"robust,":[48],"adaptation.":[50],"It":[51,75],"combines":[52],"self-training":[53],"with":[54,63],"continual":[55],"learning,":[56],"allowing":[57],"model":[59],"to":[60,97,100,144],"daily":[61],"align":[62],"user\u2019s":[65],"evolving":[66],"gait":[67],"learning":[69],"from":[70,110,142],"readily":[71],"available":[72],"unlabeled":[73,102],"data.":[74],"features":[76],"specialized":[78],"transformer":[79],"network":[80],"radar":[82],"spectrogram":[83],"analysis":[84],"novel":[87],"two-stage":[88],"labeling":[89],"algorithm":[90],"leverages":[92],"gait\u2019s":[94],"hierarchical":[95],"assign":[98],"pseudo-labels":[99],"data":[103],"accurately.":[104],"Evaluated":[105],"on":[106],"three":[107],"challenging":[108],"datasets":[109],"47":[111],"volunteers":[112],"(covering":[113],"12":[114],"gait-covariates,":[115],"11":[116],"routes,":[117],"two":[119],"weeks),":[120],"FlowGait":[121],"achieves":[122],"high":[123],"accuracies":[124],"94.8":[126],"(cross-covariate),":[127],"98.6%":[128],"(cross-route),":[129],"95.5%":[131],"(cross-day).":[132],"Notably,":[133],"dataset,":[137],"it":[138],"reduced":[139],"performance":[140],"decay":[141],"13.6%":[143],"just":[145],"1.4%,":[146],"demonstrating":[147],"real-world":[149],"robustness.":[150]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-14T00:00:00"}
