{"id":"https://openalex.org/W2963661549","doi":"https://doi.org/10.1609/aaai.v33i01.33018981","title":"Learning Non-Uniform Hypergraph for Multi-Object Tracking","display_name":"Learning Non-Uniform Hypergraph for Multi-Object Tracking","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2963661549","doi":"https://doi.org/10.1609/aaai.v33i01.33018981","mag":"2963661549"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33018981","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018981","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4928/4801","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/4928/4801","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018942445","display_name":"Longyin Wen","orcid":"https://orcid.org/0000-0001-5525-492X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Longyin Wen","raw_affiliation_strings":["JD Finance"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Finance","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027501592","display_name":"Dawei Du","orcid":"https://orcid.org/0000-0001-9404-524X"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dawei Du","raw_affiliation_strings":["University at Albany, SUNY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany, SUNY","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052126480","display_name":"Shengkun Li","orcid":"https://orcid.org/0000-0001-5458-0811"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shengkun Li","raw_affiliation_strings":["University at Albany, SUNY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany, SUNY","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085010505","display_name":"Xiao Bian","orcid":"https://orcid.org/0000-0001-5447-6045"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Bian","raw_affiliation_strings":["GE Global Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"GE Global Research","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023752172","display_name":"Siwei Lyu","orcid":"https://orcid.org/0000-0002-0992-685X"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siwei Lyu","raw_affiliation_strings":["University at Albany, SUNY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany, SUNY","institution_ids":["https://openalex.org/I392282"]}]}],"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":41,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"01","first_page":"8981","last_page":"8988"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9984999895095825,"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":0.9984999895095825,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9315000176429749,"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/hypergraph","display_name":"Hypergraph","score":0.925989031791687},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8035800457000732},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6851001381874084},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6594923138618469},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6100467443466187},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5936955213546753},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5670360922813416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5196881890296936},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.48522070050239563},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.45148521661758423},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3804696202278137},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37258589267730713},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35687994956970215},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21528387069702148}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.925989031791687},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8035800457000732},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6851001381874084},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6594923138618469},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6100467443466187},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5936955213546753},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5670360922813416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5196881890296936},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.48522070050239563},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.45148521661758423},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3804696202278137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37258589267730713},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35687994956970215},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21528387069702148},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33018981","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018981","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4928/4801","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/4928","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4928","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"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33018981","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33018981","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4928/4801","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":[{"id":"https://metadata.un.org/sdg/16","score":0.5799999833106995,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G3685593106","display_name":"\u57fa\u4e8e\u9ad8\u9636\u4fe1\u606f\u7684\u89c6\u89c9\u76ee\u6807\u8ddf\u8e2a\u7814\u7a76","funder_award_id":"61771341","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3735786873","display_name":"RI:Small: Online Maximization Algorithms for Streaming Data","funder_award_id":"1816227","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7161131930","display_name":null,"funder_award_id":"IIS-1816227","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963661549.pdf","grobid_xml":"https://content.openalex.org/works/W2963661549.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1528063097","https://openalex.org/W1531192956","https://openalex.org/W1932380673","https://openalex.org/W1977830275","https://openalex.org/W2016135469","https://openalex.org/W2031248101","https://openalex.org/W2041875597","https://openalex.org/W2057568004","https://openalex.org/W2097117768","https://openalex.org/W2104828970","https://openalex.org/W2107196083","https://openalex.org/W2115734113","https://openalex.org/W2124781496","https://openalex.org/W2127084114","https://openalex.org/W2134529534","https://openalex.org/W2160372426","https://openalex.org/W2163605009","https://openalex.org/W2163937424","https://openalex.org/W2171243491","https://openalex.org/W2209193152","https://openalex.org/W2217690257","https://openalex.org/W2225887246","https://openalex.org/W2237765446","https://openalex.org/W2291627510","https://openalex.org/W2323401846","https://openalex.org/W2343841668","https://openalex.org/W2468912036","https://openalex.org/W2511791013","https://openalex.org/W2520234541","https://openalex.org/W2547098537","https://openalex.org/W2579024533","https://openalex.org/W2739491435","https://openalex.org/W2743029672","https://openalex.org/W2749203358","https://openalex.org/W2758721842","https://openalex.org/W2797915683","https://openalex.org/W2805447362","https://openalex.org/W2963216120","https://openalex.org/W2963481014","https://openalex.org/W6641939000","https://openalex.org/W6658029077","https://openalex.org/W6674914833","https://openalex.org/W6675858769","https://openalex.org/W6677748110","https://openalex.org/W6690110275","https://openalex.org/W6696672603","https://openalex.org/W6736345168","https://openalex.org/W6752350875"],"related_works":["https://openalex.org/W2542007731","https://openalex.org/W4285271403","https://openalex.org/W2968379562","https://openalex.org/W3156013036","https://openalex.org/W4388689193","https://openalex.org/W2892070025","https://openalex.org/W29633852","https://openalex.org/W2091015105","https://openalex.org/W2985362983","https://openalex.org/W2110899030"],"abstract_inverted_index":{"The":[0,58],"majority":[1],"of":[2,50,76,82,86],"Multi-Object":[3],"Tracking":[4],"(MOT)":[5],"algorithms":[6],"based":[7,41],"on":[8,42,109],"the":[9,61,65,68,84,97,130],"tracking-by-detection":[10],"scheme":[11],"do":[12],"not":[13],"use":[14],"higher":[15],"order":[16],"dependencies":[17,51,77],"among":[18,52,78],"objects":[19],"or":[20],"tracklets,":[21],"which":[22,45],"makes":[23],"them":[24],"less":[25],"effective":[26],"in":[27,54,60],"handling":[28],"complex":[29],"scenarios.":[30],"In":[31],"this":[32],"work,":[33],"we":[34],"present":[35],"a":[36,55],"new":[37],"near-online":[38],"MOT":[39,132],"algorithm":[40,102],"non-uniform":[43],"hypergraph,":[44],"can":[46],"model":[47],"different":[48,71,89],"degrees":[49,72,90],"tracklets":[53,66],"unified":[56],"objective.":[57],"nodes":[59],"hypergraph":[62],"correspond":[63],"to":[64,121],"and":[67,118],"hyperedges":[69,87],"with":[70,88],"encode":[73],"various":[74,110],"kinds":[75],"them.":[79],"Specifically,":[80],"instead":[81],"setting":[83],"weights":[85],"empirically,":[91],"they":[92],"are":[93,106],"learned":[94],"automatically":[95],"using":[96],"structural":[98],"support":[99],"vector":[100],"machine":[101],"(SSVM).":[103],"Several":[104],"experiments":[105],"carried":[107],"out":[108],"challenging":[111],"datasets":[112],"(i.e.,":[113],"PETS09,":[114],"ParkingLot":[115],"sequence,":[116],"SubwayFace,":[117],"MOT16":[119],"benchmark),":[120],"demonstrate":[122],"that":[123],"our":[124],"method":[125],"achieves":[126],"favorable":[127],"performance":[128],"against":[129],"state-of-the-art":[131],"methods.":[133]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}