{"id":"https://openalex.org/W2761597567","doi":"https://doi.org/10.1109/tits.2017.2745683","title":"Joint Headlight Pairing and Vehicle Tracking by Weighted Set Packing in Nighttime Traffic Videos","display_name":"Joint Headlight Pairing and Vehicle Tracking by Weighted Set Packing in Nighttime Traffic Videos","publication_year":2017,"publication_date":"2017-10-03","ids":{"openalex":"https://openalex.org/W2761597567","doi":"https://doi.org/10.1109/tits.2017.2745683","mag":"2761597567"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2017.2745683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2745683","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","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/A5101696368","display_name":"Qi Zou","orcid":"https://orcid.org/0000-0002-8070-5267"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qi Zou","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061469520","display_name":"Haibin Ling","orcid":"https://orcid.org/0000-0003-4094-8413"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibin Ling","raw_affiliation_strings":["Department of Computer and Information Science, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101703057","display_name":"Yu Pang","orcid":"https://orcid.org/0000-0003-0959-2252"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Pang","raw_affiliation_strings":["Department of Computer and Information Science, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005101751","display_name":"Yaping Huang","orcid":"https://orcid.org/0000-0002-4465-372X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaping Huang","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101988621","display_name":"Mei Tian","orcid":"https://orcid.org/0000-0002-7388-3954"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mei Tian","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101696368"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":1.0012,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.85281653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"19","issue":"6","first_page":"1950","last_page":"1961"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9988999962806702,"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":0.9988999962806702,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/pairing","display_name":"Pairing","score":0.8478870391845703},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6630071997642517},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5962042808532715},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5562270283699036},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.5251952409744263},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5167931318283081},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4570375680923462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4380429983139038},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.4134679138660431},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4083852767944336},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3925778865814209},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2113390862941742},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21048977971076965}],"concepts":[{"id":"https://openalex.org/C14103023","wikidata":"https://www.wikidata.org/wiki/Q11681459","display_name":"Pairing","level":3,"score":0.8478870391845703},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6630071997642517},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5962042808532715},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5562270283699036},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.5251952409744263},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5167931318283081},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4570375680923462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4380429983139038},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.4134679138660431},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4083852767944336},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3925778865814209},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2113390862941742},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21048977971076965},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C54101563","wikidata":"https://www.wikidata.org/wiki/Q124131","display_name":"Superconductivity","level":2,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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":1,"locations":[{"id":"doi:10.1109/tits.2017.2745683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2745683","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3191323954","display_name":null,"funder_award_id":"2016JBM016","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3693879949","display_name":null,"funder_award_id":"61370127","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4382773282","display_name":null,"funder_award_id":"IIS-1449860","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4766131258","display_name":null,"funder_award_id":"61472029","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5367251961","display_name":null,"funder_award_id":"CNS-1618398","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6445190073","display_name":null,"funder_award_id":"61473031","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7933405493","display_name":null,"funder_award_id":"2015JBM036","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8978550248","display_name":null,"funder_award_id":"IIS-1350521","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/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W123871882","https://openalex.org/W1568122762","https://openalex.org/W1571268436","https://openalex.org/W1637724323","https://openalex.org/W1966136723","https://openalex.org/W1982285397","https://openalex.org/W2014898029","https://openalex.org/W2018776447","https://openalex.org/W2025665395","https://openalex.org/W2036721747","https://openalex.org/W2044764873","https://openalex.org/W2094198769","https://openalex.org/W2100548006","https://openalex.org/W2115739848","https://openalex.org/W2117942072","https://openalex.org/W2121487475","https://openalex.org/W2124659883","https://openalex.org/W2124781496","https://openalex.org/W2127084114","https://openalex.org/W2127782573","https://openalex.org/W2133856449","https://openalex.org/W2151875803","https://openalex.org/W2161086211","https://openalex.org/W2237765446","https://openalex.org/W2343104654","https://openalex.org/W2471389393","https://openalex.org/W3097096317","https://openalex.org/W6634116786","https://openalex.org/W6656781311"],"related_works":["https://openalex.org/W3015473028","https://openalex.org/W3201176751","https://openalex.org/W2057898405","https://openalex.org/W2029180842","https://openalex.org/W2051379014","https://openalex.org/W2953807518","https://openalex.org/W1993094293","https://openalex.org/W2258335979","https://openalex.org/W2890366349","https://openalex.org/W3119345543"],"abstract_inverted_index":{"We":[0],"propose":[1,58],"a":[2,66,71,100,106],"set":[3],"packing":[4],"(SP)":[5],"framework":[6],"for":[7,50,91,97],"joint":[8,156],"headlight":[9,15,41],"pairing":[10,113],"and":[11,26,43,83,93,111,117,177,193],"vehicle":[12,19,51,109,123,191],"tracking.":[13,52],"Given":[14],"detections,":[16],"traditional":[17],"nighttime":[18,190],"tracking":[20,92,192],"methods":[21],"usually":[22],"first":[23],"pair":[24,78],"headlights":[25],"then":[27],"track":[28,79,139],"these":[29,62],"pairs.":[30],"However,":[31],"the":[32,55,88,94,129,136,155,198,203],"poor":[33],"photometric":[34],"condition":[35],"often":[36],"introduces":[37],"tremendous":[38],"noises":[39],"in":[40,65,85,118,189,194],"detection":[42],"pairing,":[44],"which":[45,75],"leads":[46],"to":[47,59,153],"unrecoverable":[48],"errors":[49],"To":[53,145],"overcome":[54],"challenge,":[56],"we":[57],"jointly":[60,201],"model":[61,157],"two":[63,165,204],"tasks":[64],"weighted":[67,101],"SP":[68,102],"framework.":[69],"Specifically,":[70],"graph":[72,107,133],"is":[73,162],"built":[74],"takes":[76],"candidate":[77],"hypotheses":[80,140],"as":[81],"nodes":[82],"encodes":[84],"edges":[86],"both":[87,188],"disjoint":[89],"constraints":[90,96],"no-sharing-headlight":[95],"pairing.":[98],"Solving":[99],"problem":[103],"on":[104,164],"such":[105],"produces":[108,120],"trajectories,":[110],"facilitates":[112],"with":[114],"temporal":[115],"context":[116],"turn":[119],"high":[121],"quality":[122],"trajectories.":[124],"The":[125,159],"solution,":[126],"however,":[127],"raises":[128],"issue":[130],"of":[131,138,200],"unmanageable":[132],"scale":[134],"since":[135],"number":[137],"grows":[141],"exponentially":[142],"over":[143],"time.":[144],"address":[146],"this":[147],"issue,":[148],"pruning":[149],"strategies":[150],"are":[151],"developed":[152],"solve":[154],"efficiently.":[158],"proposed":[160],"system":[161],"evaluated":[163],"traffic":[166],"data":[167],"sets,":[168],"including":[169],"videos":[170],"under":[171],"various":[172],"challenging":[173],"conditions.":[174],"Both":[175],"quantitative":[176],"qualitative":[178],"results":[179],"show":[180],"that":[181],"our":[182],"method":[183],"outperforms":[184],"other":[185],"tested":[186],"methods,":[187],"multi-target":[195],"tracking,":[196],"confirming":[197],"benefits":[199],"modeling":[202],"tasks.":[205]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
