{"id":"https://openalex.org/W7161696606","doi":"https://doi.org/10.1109/access.2026.3694943","title":"Real-Time Pedestrian Detection and Multi-Object Tracking in Complex Airport Scenes via Frequency-Aware and Mamba-Enhanced Representation","display_name":"Real-Time Pedestrian Detection and Multi-Object Tracking in Complex Airport Scenes via Frequency-Aware and Mamba-Enhanced Representation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7161696606","doi":"https://doi.org/10.1109/access.2026.3694943"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3694943","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3694943","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3694943","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100999204","display_name":"Zhou Can","orcid":null},"institutions":[{"id":"https://openalex.org/I2799537086","display_name":"Manchester Airport","ror":"https://ror.org/01wbcv120","country_code":"GB","type":"other","lineage":["https://openalex.org/I2799537086"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Can Zhou","raw_affiliation_strings":["Expand Construction Command Department, Chongqing Airport Group Company Ltd., Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Expand Construction Command Department, Chongqing Airport Group Company Ltd., Chongqing, China","institution_ids":["https://openalex.org/I2799537086"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078615305","display_name":"Kehua Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128665","display_name":"ISCO International (United States)","ror":"https://ror.org/03p9zdb14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210128665"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kehua Liu","raw_affiliation_strings":["Nanjing Lukou International Airport Technology Company Ltd., Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0008-5261-1715","affiliations":[{"raw_affiliation_string":"Nanjing Lukou International Airport Technology Company Ltd., Nanjing, China","institution_ids":["https://openalex.org/I4210128665"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136496286","display_name":"Kefei Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128665","display_name":"ISCO International (United States)","ror":"https://ror.org/03p9zdb14","country_code":"US","type":"company","lineage":["https://openalex.org/I4210128665"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kefei Hu","raw_affiliation_strings":["Nanjing Lukou International Airport Technology Company Ltd., Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing Lukou International Airport Technology Company Ltd., Nanjing, China","institution_ids":["https://openalex.org/I4210128665"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124073596","display_name":"Hai Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I2799537086","display_name":"Manchester Airport","ror":"https://ror.org/01wbcv120","country_code":"GB","type":"other","lineage":["https://openalex.org/I2799537086"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hai Wang","raw_affiliation_strings":["Expand Construction Command Department, Chongqing Airport Group Company Ltd., Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Expand Construction Command Department, Chongqing Airport Group Company Ltd., Chongqing, China","institution_ids":["https://openalex.org/I2799537086"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59330168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"82731","last_page":"82748"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.527400016784668,"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":0.527400016784668,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.22259999811649323,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.043299999088048935,"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/pedestrian-detection","display_name":"Pedestrian detection","score":0.5940999984741211},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5734000205993652},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5659000277519226},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5575000047683716},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5072000026702881},{"id":"https://openalex.org/keywords/radar-tracker","display_name":"Radar tracker","score":0.32919999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7670000195503235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7577999830245972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6973000168800354},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5940999984741211},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5734000205993652},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5659000277519226},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5575000047683716},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5072000026702881},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3181999921798706},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.3034999966621399},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.2685000002384186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.26570001244544983},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.25859999656677246}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3694943","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3694943","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7d56ad1cbc3f4f08901bb729b1ed1e0c","is_oa":true,"landing_page_url":"https://doaj.org/article/7d56ad1cbc3f4f08901bb729b1ed1e0c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 82731-82748 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3694943","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3694943","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.732866108417511,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320330736","display_name":"Petrochemical Research and Technology Company","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Real-time":[0],"pedestrian":[1,57,197],"detection":[2],"and":[3,23,36,120,132,146,179,192,206,245,272],"multi-object":[4],"tracking":[5,174],"(MOT)":[6],"in":[7,39,106],"complex":[8],"airport":[9,181,249,277],"surveillance":[10],"scenarios":[11],"present":[12],"significant":[13],"challenges,":[14,46],"including":[15],"drastic":[16],"scale":[17],"variation,":[18],"frequent":[19],"occlusion,":[20],"cluttered":[21],"backgrounds,":[22],"diverse":[24],"motion":[25,154,171,239],"dynamics.":[26],"Existing":[27],"methods":[28,258],"often":[29],"fail":[30],"to":[31,75,102,150,163,195],"simultaneously":[32],"satisfy":[33],"accuracy,":[34],"robustness,":[35],"real-time":[37,264],"requirements":[38],"such":[40],"demanding":[41],"environments.":[42],"To":[43],"address":[44],"these":[45],"we":[47,60,87,136,185],"propose":[48],"AirMOTR,":[49],"a":[50,62,219,270],"unified":[51],"detection-and-tracking":[52],"framework":[53],"tailored":[54],"for":[55,176,238,275],"airport-scene":[56],"perception.":[58],"First,":[59],"integrate":[61],"lightweight":[63],"two-dimensional":[64],"Selective":[65],"State":[66],"Space":[67],"Model":[68],"(SS2D)":[69],"into":[70],"the":[71,107,189,210,243],"backbone":[72],"feature":[73,91,104,127,198],"extractor":[74],"efficiently":[76],"capture":[77],"long-range":[78],"spatial":[79,131,225,244],"dependencies":[80,226],"while":[81,230,262],"maintaining":[82,263],"low":[83],"computational":[84],"overhead.":[85],"Second,":[86],"introduce":[88],"three":[89],"complementary":[90,220],"enhancement":[92],"modules:":[93],"aFrequency-aware":[94],"Interaction":[95],"Block(FIB)":[96],"that":[97,113,124,254],"employs":[98],"discrete":[99],"wavelet":[100],"transform":[101],"enrich":[103],"representations":[105],"frequency":[108],"domain;":[109],"aQuery-driven":[110],"Context":[111],"Extractor(QCE)":[112],"aggregates":[114],"contextual":[115],"semantics":[116],"through":[117],"detection-query":[118],"guidance;":[119],"anAdaptive":[121],"Spatial-Channel":[122],"Gate(ASCG)":[123],"dynamically":[125],"modulates":[126],"responses":[128],"across":[129,235],"both":[130,177],"channel":[133],"dimensions.":[134],"Third,":[135],"embed":[137],"theMotion":[138],"Mamba(MM)":[139],"module":[140],"within":[141,227],"MM-Tracker,":[142],"combining":[143],"local":[144],"correlation":[145],"global":[147,224],"bidirectional":[148,233],"scanning":[149,234],"generate":[151],"accurate":[152],"inter-frame":[153],"maps.":[155],"A":[156],"novelMotion":[157],"Margin":[158],"Loss(MMLoss)":[159],"is":[160,280],"also":[161],"proposed":[162],"adaptively":[164],"adjust":[165],"association":[166],"boundaries":[167],"based":[168],"on":[169,188,202,209,259],"per-target":[170],"magnitude,":[172],"improving":[173],"robustness":[175],"slow-moving":[178],"fast-moving":[180],"passengers.":[182],"For":[183],"training,":[184],"first":[186],"pre-train":[187],"large-scale":[190],"CrowdHuman":[191],"WiderPedestrian":[193],"datasets":[194],"strengthen":[196],"generalization,":[199],"then":[200],"fine-tune":[201],"our":[203],"newly":[204],"constructedAirportPassengerdataset":[205],"validate":[207],"generalizability":[208],"ASS":[211],"(Airport":[212],"Security":[213],"Surveillance)":[214],"dataset.":[215],"Notably,":[216],"SS2D":[217,222],"andMMform":[218],"pair:":[221],"captures":[223],"individual":[228],"frames,":[229],"MM":[231],"leverages":[232],"temporal":[236,246],"frames":[237],"modeling,":[240],"jointly":[241],"addressing":[242],"challenges":[247],"of":[248],"surveillance.":[250,278],"Extensive":[251],"experiments":[252],"demonstrate":[253],"AirMOTR":[255],"outperforms":[256],"state-of-the-art":[257],"all":[260],"benchmarks":[261],"inference":[265],"speed":[266],"(\u224841.6":[267],"FPS),":[268],"providing":[269],"robust":[271],"practical":[273],"solution":[274],"intelligent":[276],"Code":[279],"available":[281],"at":[282],"https://github.com/zhoucancqa/AirMOTR.":[283]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2026-05-20T00:00:00"}