{"id":"https://openalex.org/W4390031035","doi":"https://doi.org/10.1109/ist59124.2023.10355705","title":"TunnelTrack: A Dataset for Multi-Object Tracking in Tunnel Roads","display_name":"TunnelTrack: A Dataset for Multi-Object Tracking in Tunnel Roads","publication_year":2023,"publication_date":"2023-10-17","ids":{"openalex":"https://openalex.org/W4390031035","doi":"https://doi.org/10.1109/ist59124.2023.10355705"},"language":"en","primary_location":{"id":"doi:10.1109/ist59124.2023.10355705","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ist59124.2023.10355705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Imaging Systems and Techniques (IST)","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/A5101311737","display_name":"Jiayi Zhuo","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":"Jiayi Zhuo","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049440204","display_name":"Jiayang Huang","orcid":"https://orcid.org/0000-0002-0905-0915"},"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":"Jiayang Huang","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013482491","display_name":"Lihui Peng","orcid":"https://orcid.org/0000-0001-7363-6374"},"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":"Lihui Peng","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443501","display_name":"Shuang Chen","orcid":"https://orcid.org/0000-0002-5452-194X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuang Chen","raw_affiliation_strings":["Guihou Door To Time Science And Technology Co.,Ltd,Guiyang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guihou Door To Time Science And Technology Co.,Ltd,Guiyang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081663090","display_name":"Danya Yao","orcid":"https://orcid.org/0000-0001-5032-6322"},"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":"Danya Yao","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100688166","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-1113-8465"},"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":"Yi Zhang","raw_affiliation_strings":["Tsinghua University,Department of Automation,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Department of Automation,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9787999987602234,"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":0.9787999987602234,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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":0.939300000667572,"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":0.703657865524292},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5842389464378357},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5163070559501648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48425623774528503},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4743993282318115},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.46388062834739685}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703657865524292},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5842389464378357},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5163070559501648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48425623774528503},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4743993282318115},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.46388062834739685},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ist59124.2023.10355705","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ist59124.2023.10355705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Imaging Systems and Techniques (IST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1521019969","https://openalex.org/W1861492603","https://openalex.org/W2115579991","https://openalex.org/W2124781496","https://openalex.org/W2252355370","https://openalex.org/W2603203130","https://openalex.org/W2892614179","https://openalex.org/W2963037989","https://openalex.org/W3012922853","https://openalex.org/W3035172746","https://openalex.org/W3035564946","https://openalex.org/W3084173793","https://openalex.org/W3097885906","https://openalex.org/W3104218139","https://openalex.org/W3106763294","https://openalex.org/W3115390238","https://openalex.org/W3116469262","https://openalex.org/W3208645658","https://openalex.org/W4226272687","https://openalex.org/W4295331127","https://openalex.org/W4312689495","https://openalex.org/W4313072323","https://openalex.org/W4321231425","https://openalex.org/W4385245566","https://openalex.org/W6739901393","https://openalex.org/W6775253321","https://openalex.org/W6788023325","https://openalex.org/W6810974023"],"related_works":["https://openalex.org/W2755342338","https://openalex.org/W2058170566","https://openalex.org/W2036807459","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2079911747"],"abstract_inverted_index":{"Multi-object":[0,10],"tracking":[1,11,29,67,108],"is":[2,33,49,102],"a":[3,50,64],"very":[4],"important":[5],"field":[6],"in":[7,30,83,115],"computer":[8],"vision.":[9],"under":[12],"different":[13,16,20],"scenes":[14,82],"plays":[15],"roles":[17],"and":[18,42,55,79,122],"has":[19],"significance.":[21],"As":[22],"one":[23],"of":[24,52,88,113],"the":[25,106,111],"special":[26],"scenes,":[27],"multi-object":[28,66,107],"tunnel":[31,65,89],"roads":[32],"helpful":[34,103],"to":[35,110],"detect":[36],"abnormal":[37],"events,":[38],"reduce":[39],"traffic":[40,44],"accidents":[41],"improve":[43],"safety.":[45],"However,":[46],"currently":[47],"there":[48],"shortage":[51],"related":[53],"research":[54],"corresponding":[56],"datasets.":[57],"To":[58],"address":[59],"this":[60],"issue,":[61],"we":[62],"construct":[63],"dataset,":[68],"also":[69],"called":[70],"\"TunnelTrack\",":[71],"which":[72],"contains":[73],"more":[74],"than":[75],"20k":[76],"picture":[77],"frames":[78],"provide":[80],"rich":[81],"blur,":[84,120],"halo,":[85],"lighting":[86,124],"conditions":[87],"from":[90],"fixed":[91],"cameras.":[92],"In":[93],"addition,":[94],"preliminary":[95],"experimental":[96],"results":[97],"have":[98],"shown":[99],"that":[100],"TunnelTrack":[101],"for":[104],"addressing":[105],"due":[109],"lack":[112],"data":[114],"complex":[116],"scenarios":[117],"with":[118],"motion":[119],"glare,":[121],"challenging":[123],"conditions.":[125]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
