{"id":"https://openalex.org/W4361802102","doi":"https://doi.org/10.1109/tmm.2023.3262975","title":"Automatic Identification of Human Subgroups in Time-Dependent Pedestrian Flow Networks","display_name":"Automatic Identification of Human Subgroups in Time-Dependent Pedestrian Flow Networks","publication_year":2023,"publication_date":"2023-03-29","ids":{"openalex":"https://openalex.org/W4361802102","doi":"https://doi.org/10.1109/tmm.2023.3262975"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3262975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3262975","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.1109/TMM.2023.3262975","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070871403","display_name":"Wenhan Wu","orcid":"https://orcid.org/0000-0003-4487-9283"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenhan Wu","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011894475","display_name":"Wenfeng Yi","orcid":"https://orcid.org/0000-0003-1084-3047"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenfeng Yi","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082225017","display_name":"Jinghai Li","orcid":"https://orcid.org/0000-0002-6655-3228"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghai Li","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068635855","display_name":"Maoyin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maoyin Chen","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077134287","display_name":"Xiaoping Zheng","orcid":"https://orcid.org/0000-0002-2935-9514"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoping Zheng","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070871403"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":1.0438,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80526051,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"26","issue":null,"first_page":"166","last_page":"177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.823279857635498},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6759706139564514},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6145376563072205},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5525944232940674},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4980490207672119},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.45997974276542664},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4542274475097656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4307517409324646},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4302974343299866},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37970179319381714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10720565915107727},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.08715429902076721}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.823279857635498},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6759706139564514},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6145376563072205},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5525944232940674},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4980490207672119},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.45997974276542664},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4542274475097656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4307517409324646},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4302974343299866},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37970179319381714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10720565915107727},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.08715429902076721},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tmm.2023.3262975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3262975","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"},{"id":"pmh:oai:zenodo.org:13956820","is_oa":true,"landing_page_url":"https://doi.org/10.1109/TMM.2023.3262975","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Multimedia, 26, 166-177, (2023-03-29)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:13956820","is_oa":true,"landing_page_url":"https://doi.org/10.1109/TMM.2023.3262975","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Multimedia, 26, 166-177, (2023-03-29)","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W1908017399","https://openalex.org/W1970206276","https://openalex.org/W1988920820","https://openalex.org/W2017528889","https://openalex.org/W2026031825","https://openalex.org/W2036721747","https://openalex.org/W2040819715","https://openalex.org/W2047940964","https://openalex.org/W2053045874","https://openalex.org/W2061083018","https://openalex.org/W2063929853","https://openalex.org/W2089584121","https://openalex.org/W2091202730","https://openalex.org/W2095293504","https://openalex.org/W2110620844","https://openalex.org/W2121947440","https://openalex.org/W2127048411","https://openalex.org/W2128366083","https://openalex.org/W2132505539","https://openalex.org/W2141841319","https://openalex.org/W2148606196","https://openalex.org/W2148961728","https://openalex.org/W2164727176","https://openalex.org/W2164928285","https://openalex.org/W2168878667","https://openalex.org/W2171901700","https://openalex.org/W2172252186","https://openalex.org/W2174397525","https://openalex.org/W2217748804","https://openalex.org/W2311915351","https://openalex.org/W2328972779","https://openalex.org/W2342822214","https://openalex.org/W2476479720","https://openalex.org/W2511264812","https://openalex.org/W2516753716","https://openalex.org/W2532516272","https://openalex.org/W2606987052","https://openalex.org/W2759089887","https://openalex.org/W2766748881","https://openalex.org/W2767472986","https://openalex.org/W2784186719","https://openalex.org/W2793868694","https://openalex.org/W2888776864","https://openalex.org/W2901862856","https://openalex.org/W2945187923","https://openalex.org/W2948683146","https://openalex.org/W3027678042","https://openalex.org/W3044673138","https://openalex.org/W3088236174","https://openalex.org/W3102641634","https://openalex.org/W3201039332","https://openalex.org/W3207440712","https://openalex.org/W6600188635"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W1976827262","https://openalex.org/W49697837","https://openalex.org/W3122828758","https://openalex.org/W2170799233","https://openalex.org/W2768112316","https://openalex.org/W4205958986"],"abstract_inverted_index":{"The":[0,57],"study":[1],"of":[2,17,50,86,130,136,142,154,160],"identifying":[3],"human":[4,51,102],"subgroups":[5,52,103],"from":[6],"videos":[7],"is":[8,79,93],"a":[9,15,43,74],"significant":[10],"topic,":[11],"which":[12,73],"has":[13,26],"received":[14],"lot":[16],"attention":[18],"in":[19,36,53,104,128],"multiple":[20],"disciplines.":[21],"So":[22],"far,":[23],"however,":[24],"there":[25],"been":[27],"little":[28],"consideration":[29],"about":[30],"combining":[31],"it":[32],"with":[33],"relevant":[34],"conceptions":[35],"network":[37,78],"science.":[38],"Therefore,":[39],"this":[40,146],"article":[41],"proposes":[42],"novel":[44],"method":[45,112],"for":[46,151],"the":[47,67,83,90,152,158],"automatic":[48],"identification":[49,115],"dynamic":[54],"pedestrian":[55,76],"flows.":[56],"spatial":[58],"proximity":[59],"and":[60,121,139,157],"temporal":[61],"continuity":[62],"are":[63],"combined":[64],"to":[65,95,101],"calculate":[66],"interaction":[68],"intensity":[69],"between":[70],"pedestrians,":[71],"by":[72],"time-dependent":[75],"flow":[77],"constructed.":[80],"Based":[81],"on":[82],"objective":[84],"function":[85],"weighted":[87],"partition":[88],"density,":[89],"optimal":[91],"threshold":[92],"used":[94],"determine":[96],"community":[97],"structures":[98],"that":[99,110],"correspond":[100],"frame":[105],"images.":[106],"Numerical":[107],"experiments":[108],"demonstrate":[109],"our":[111],"achieves":[113],"high":[114],"accuracy":[116],"under":[117],"various":[118,134],"evaluation":[119],"datasets,":[120],"exhibits":[122],"better":[123],"performance":[124],"than":[125],"existing":[126],"methods":[127],"terms":[129],"different":[131],"crowd":[132],"densities,":[133],"numbers":[135],"subgroup":[137,155,161],"members,":[138],"certain":[140],"levels":[141],"trajectory":[143],"noise.":[144],"Furthermore,":[145],"work":[147],"provides":[148],"valuable":[149],"implications":[150],"understanding":[153],"behaviors":[156],"modeling":[159],"movements.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}