{"id":"https://openalex.org/W2904427185","doi":"https://doi.org/10.1609/aaai.v33i01.33018738","title":"A Bottom-Up Clustering Approach to Unsupervised Person Re-Identification","display_name":"A Bottom-Up Clustering Approach to Unsupervised Person Re-Identification","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2904427185","doi":"https://doi.org/10.1609/aaai.v33i01.33018738","mag":"2904427185"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33018738","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018738","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4898/4771","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4898/4771","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045116626","display_name":"Yutian Lin","orcid":"https://orcid.org/0000-0002-0643-0533"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yutian Lin","raw_affiliation_strings":["University of Technology Sydney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology Sydney","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069837273","display_name":"Xuanyi Dong","orcid":"https://orcid.org/0000-0001-9272-1590"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xuanyi Dong","raw_affiliation_strings":["University of Technology, Sydney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Sydney","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100709340","display_name":"Liang Zheng","orcid":"https://orcid.org/0000-0002-1464-9500"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Liang Zheng","raw_affiliation_strings":["Australian National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Australian National University","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395059","display_name":"Yan Yan","orcid":"https://orcid.org/0000-0002-3674-7160"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Yan","raw_affiliation_strings":["Texas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas State University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005421447","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0002-0512-880X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":["University of Technology, Sydney"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Sydney","institution_ids":["https://openalex.org/I114017466"]}]}],"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":true,"cited_by_count":597,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"01","first_page":"8738","last_page":"8745"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9907000064849854,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9882000088691711,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7230372428894043},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6671463847160339},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6020448803901672},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5438873767852783},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.521169900894165},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.46466124057769775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4575127959251404},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.42881470918655396},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4252578914165497},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.41596975922584534},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3341420292854309},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1903926134109497}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230372428894043},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6671463847160339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6020448803901672},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5438873767852783},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.521169900894165},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.46466124057769775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4575127959251404},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.42881470918655396},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4252578914165497},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.41596975922584534},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3341420292854309},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1903926134109497},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1609/aaai.v33i01.33018738","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018738","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4898/4771","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/4898","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4898","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:openresearch-repository.anu.edu.au:1885/313739","is_oa":false,"landing_page_url":"http://hdl.handle.net/1885/313739","pdf_url":null,"source":{"id":"https://openalex.org/S4306402539","display_name":"ANU Open Research (Australian National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I118347636","host_organization_name":"Australian National University","host_organization_lineage":["https://openalex.org/I118347636"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 33rd AAAI Conference on Artificial Intelligence","raw_type":"Conference paper"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/139762","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/139762","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33018738","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018738","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4898/4771","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320307791","display_name":"Cisco Systems","ror":"https://ror.org/03yt1ez60"},{"id":"https://openalex.org/F4320335741","display_name":"Data to Decisions Cooperative Research Centres","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W82130502","https://openalex.org/W1590510366","https://openalex.org/W1644402181","https://openalex.org/W1821462560","https://openalex.org/W1897044480","https://openalex.org/W1949591461","https://openalex.org/W1963702692","https://openalex.org/W1979260620","https://openalex.org/W1982925187","https://openalex.org/W1991452654","https://openalex.org/W2009907187","https://openalex.org/W2046835352","https://openalex.org/W2079972027","https://openalex.org/W2135442311","https://openalex.org/W2148349024","https://openalex.org/W2163605009","https://openalex.org/W2173520492","https://openalex.org/W2187089797","https://openalex.org/W2204750386","https://openalex.org/W2327827989","https://openalex.org/W2441160157","https://openalex.org/W2462901929","https://openalex.org/W2502225121","https://openalex.org/W2511791013","https://openalex.org/W2516580127","https://openalex.org/W2520433280","https://openalex.org/W2577749540","https://openalex.org/W2585635281","https://openalex.org/W2587914376","https://openalex.org/W2591888901","https://openalex.org/W2618353479","https://openalex.org/W2754126974","https://openalex.org/W2756689160","https://openalex.org/W2769088658","https://openalex.org/W2778652957","https://openalex.org/W2793741436","https://openalex.org/W2794651663","https://openalex.org/W2798730128","https://openalex.org/W2798991696","https://openalex.org/W2799185441","https://openalex.org/W2832876791","https://openalex.org/W2888222975","https://openalex.org/W2895589658","https://openalex.org/W2962925415","https://openalex.org/W2963000559","https://openalex.org/W2963074118","https://openalex.org/W2963152148","https://openalex.org/W2963557071","https://openalex.org/W2963574614","https://openalex.org/W2963684088","https://openalex.org/W3098711604","https://openalex.org/W3118608800","https://openalex.org/W6638523607","https://openalex.org/W6679857944","https://openalex.org/W6687888618"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2804364458","https://openalex.org/W4298130764","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2132641928","https://openalex.org/W4321444604","https://openalex.org/W4310225030","https://openalex.org/W2083665254","https://openalex.org/W2811106690"],"abstract_inverted_index":{"Most":[0],"person":[1],"re-identification":[2],"(re-ID)":[3],"approaches":[4],"are":[5],"based":[6],"on":[7,154],"supervised":[8],"learning,":[9],"which":[10,96,112],"requires":[11],"intensive":[12],"manual":[13],"annotation":[14,27],"for":[15],"training":[16],"data.":[17,36],"However,":[18],"it":[19,104],"is":[20,175],"not":[21,176],"only":[22,177],"resourceintensive":[23],"to":[24,31,48,130,179],"acquire":[25],"identity":[26],"but":[28,184],"also":[29,185],"impractical":[30],"label":[32],"the":[33,57,60,70,81,98,114,126,132,139,146,155],"large-scale":[34,156],"real-world":[35],"To":[37],"relieve":[38],"this":[39],"problem,":[40],"we":[41],"propose":[42],"a":[43,51,93,121],"bottom-up":[44,127],"clustering":[45,128],"(BUC)":[46],"approach":[47],"jointly":[49],"optimize":[50],"convolutional":[52],"neural":[53],"network":[54],"(CNN)":[55],"and":[56,78,148,158,166,192],"relationship":[58],"among":[59],"individual":[61,90],"samples.":[62],"Our":[63],"algorithm":[64,86,174],"considers":[65],"two":[66],"fundamental":[67],"facts":[68],"in":[69,125],"re-ID":[71,160,182],"task,":[72],"i.e.,":[73],"diversity":[74,99,122,147],"across":[75],"different":[76,94],"identities":[77],"similarity":[79,115],"within":[80,116],"same":[82],"identity.":[83,102,118],"Specifically,":[84],"our":[85,173],"starts":[87],"with":[88],"regarding":[89],"sample":[91],"as":[92],"identity,":[95,111],"maximizes":[97],"over":[100],"each":[101,117,136],"Then":[103],"gradually":[105],"groups":[106],"similar":[107],"samples":[108],"into":[109],"one":[110],"increases":[113],"We":[119,150],"utilizes":[120],"regularization":[123],"term":[124],"procedure":[129],"balance":[131],"data":[133],"volume":[134],"of":[135],"cluster.":[137],"Finally,":[138],"model":[140],"achieves":[141],"an":[142],"effective":[143],"trade-off":[144],"between":[145],"similarity.":[149],"conduct":[151],"extensive":[152],"experiments":[153],"image":[157],"video":[159],"datasets,":[161],"including":[162],"Market-1501,":[163],"DukeMTMCreID,":[164],"MARS":[165],"DukeMTMC-VideoReID.":[167],"The":[168],"experimental":[169],"results":[170],"demonstrate":[171],"that":[172],"superior":[178],"state-of-the-art":[180],"unsupervised":[181],"approaches,":[183],"performs":[186],"favorably":[187],"than":[188],"competing":[189],"transfer":[190],"learning":[191,194],"semi-supervised":[193],"methods.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":48},{"year":2024,"cited_by_count":81},{"year":2023,"cited_by_count":97},{"year":2022,"cited_by_count":104},{"year":2021,"cited_by_count":154},{"year":2020,"cited_by_count":79},{"year":2019,"cited_by_count":26}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
