{"id":"https://openalex.org/W4293518726","doi":"https://doi.org/10.1109/icme52920.2022.9859981","title":"Decomposing Identity and View for Cross-View Gait Recognition","display_name":"Decomposing Identity and View for Cross-View Gait Recognition","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4293518726","doi":"https://doi.org/10.1109/icme52920.2022.9859981"},"language":"en","primary_location":{"id":"doi:10.1109/icme52920.2022.9859981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9859981","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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 IEEE International Conference on Multimedia and Expo (ICME)","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/A5052670860","display_name":"Xinliang Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I4210105229","display_name":"City University of Hong Kong, Shenzhen Research Institute","ror":"https://ror.org/00xc0ma20","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210105229"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinliang Zhai","raw_affiliation_strings":["Shenzhen Research Institute of Shandong University,Shenzhen,China,518063","School of Information Science and Engineering, Shandong University, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Shandong University,Shenzhen,China,518063","institution_ids":["https://openalex.org/I4210105229","https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018607913","display_name":"Xianye Ben","orcid":"https://orcid.org/0000-0001-8083-3501"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I4210105229","display_name":"City University of Hong Kong, Shenzhen Research Institute","ror":"https://ror.org/00xc0ma20","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210105229"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianye Ben","raw_affiliation_strings":["Shenzhen Research Institute of Shandong University,Shenzhen,China,518063","School of Information Science and Engineering, Shandong University, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Shandong University,Shenzhen,China,518063","institution_ids":["https://openalex.org/I4210105229","https://openalex.org/I154099455"]},{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101624842","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0001-7756-6449"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Liu","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University,Qingdao,China,266237"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University,Qingdao,China,266237","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016779836","display_name":"Tingxuan Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingxuan Xie","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University,Qingdao,China,266237"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University,Qingdao,China,266237","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":1.0,"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":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9749000072479248,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9557999968528748,"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/discriminative-model","display_name":"Discriminative model","score":0.8881974220275879},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6931846141815186},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.6801464557647705},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6577655673027039},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6506207585334778},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.648751974105835},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6189491152763367},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5604647994041443},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.46570664644241333},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.45653897523880005},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4394252598285675},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.43225225806236267},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4031803607940674},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1319778561592102},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.10948455333709717}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8881974220275879},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6931846141815186},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.6801464557647705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6577655673027039},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6506207585334778},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.648751974105835},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6189491152763367},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5604647994041443},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.46570664644241333},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.45653897523880005},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4394252598285675},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.43225225806236267},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4031803607940674},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1319778561592102},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.10948455333709717},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C42407357","wikidata":"https://www.wikidata.org/wiki/Q521","display_name":"Physiology","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"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/icme52920.2022.9859981","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9859981","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","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 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.75}],"awards":[{"id":"https://openalex.org/G249261041","display_name":null,"funder_award_id":"61971468","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5274560807","display_name":null,"funder_award_id":"2022A1515010186","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1181052087","https://openalex.org/W1603775159","https://openalex.org/W1971239273","https://openalex.org/W2038118117","https://openalex.org/W2058897916","https://openalex.org/W2063626761","https://openalex.org/W2068715223","https://openalex.org/W2075060084","https://openalex.org/W2104335344","https://openalex.org/W2149516292","https://openalex.org/W2154171558","https://openalex.org/W2322772590","https://openalex.org/W2338200236","https://openalex.org/W2437735720","https://openalex.org/W2522764072","https://openalex.org/W2766382441","https://openalex.org/W2909676093","https://openalex.org/W2909756869","https://openalex.org/W2911676551","https://openalex.org/W3008732063","https://openalex.org/W3091184187","https://openalex.org/W3128064349","https://openalex.org/W3180933213","https://openalex.org/W3182137715","https://openalex.org/W4205260486","https://openalex.org/W6636186584","https://openalex.org/W6675575696","https://openalex.org/W6682274878","https://openalex.org/W6798192689","https://openalex.org/W6798557309"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W3185413894","https://openalex.org/W1905194803","https://openalex.org/W2137411393","https://openalex.org/W1923394858"],"abstract_inverted_index":{"One":[0],"of":[1],"many":[2],"challenges":[3],"in":[4,158],"cross-view":[5,63,159],"gait":[6,32,36,50,64,160],"recognition":[7,37],"is":[8,26,121],"that":[9,35,109,152],"a":[10,55,69,118],"pedestrian's":[11],"gaits":[12],"have":[13],"huge":[14],"visual":[15],"differences":[16],"under":[17],"different":[18],"views.":[19],"A":[20],"promising":[21],"solution":[22],"to":[23,27,42,47,57,73,92,107,123,136],"this":[24,52],"challenge":[25],"extract":[28,48],"fundamental":[29],"discriminative":[30,49,94],"view-invariant":[31],"features,":[33,51],"so":[34,134],"systems":[38],"can":[39],"be":[40],"robust":[41],"viewpoint":[43],"varying.":[44],"In":[45],"order":[46],"paper":[53],"proposes":[54],"method":[56,67,155],"decompose":[58],"identity":[59,76,95,103,129,140],"and":[60,89,102,131,148],"view":[61,80,100,111,115,132],"for":[62],"recognition.":[65,161],"Our":[66],"employs":[68],"newly":[70],"designed":[71],"auto-encoder":[72],"detach":[74],"the":[75,79,87,99,110,125,139,146,153],"features":[77,112],"from":[78],"features.":[81],"We":[82],"train":[83],"our":[84],"model":[85],"with":[86],"classification":[88],"metric":[90],"learning":[91],"obtain":[93],"feature.":[96,141],"Also,":[97],"both":[98],"regression":[101],"ambiguity":[104],"are":[105],"applied":[106],"ensure":[108],"only":[113],"contain":[114],"information.":[116],"Finally,":[117],"dissimilarity":[119],"loss":[120],"proposed":[122,154],"increase":[124],"distribution":[126],"discrepancy":[127],"between":[128],"feature":[130],"feature,":[133],"as":[135],"further":[137],"refine":[138],"The":[142],"experimental":[143],"results":[144],"on":[145],"CASIA-B":[147],"OU-ISIR":[149],"databases":[150],"show":[151],"performs":[156],"well":[157]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}