{"id":"https://openalex.org/W4402352564","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650328","title":"An Instance-Level Motion-Aware Graph Model for Multi-target Multi-camera Tracking","display_name":"An Instance-Level Motion-Aware Graph Model for Multi-target Multi-camera Tracking","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352564","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650328"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5088037723","display_name":"Xiaotong Fan","orcid":"https://orcid.org/0000-0002-4811-8118"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotong Fan","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034213282","display_name":"Huicheng Zheng","orcid":"https://orcid.org/0000-0002-6729-4176"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huicheng Zheng","raw_affiliation_strings":["Sun Yat-sen University,School of Computer Science and Engineering,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University,School of Computer Science and Engineering,China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.2629,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53566139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9825000166893005,"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":0.7109758853912354},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6886324286460876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6456636190414429},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5128500461578369},{"id":"https://openalex.org/keywords/match-moving","display_name":"Match moving","score":0.4537028968334198},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44667479395866394},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.3729174733161926},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.07108202576637268}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109758853912354},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6886324286460876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6456636190414429},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5128500461578369},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.4537028968334198},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44667479395866394},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3729174733161926},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.07108202576637268},{"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/ijcnn60899.2024.10650328","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650328","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2294764595","https://openalex.org/W2473532709","https://openalex.org/W2511791013","https://openalex.org/W2603203130","https://openalex.org/W2770870020","https://openalex.org/W2896030169","https://openalex.org/W2920942303","https://openalex.org/W2962923976","https://openalex.org/W2962996864","https://openalex.org/W2963573564","https://openalex.org/W2963852441","https://openalex.org/W2967515867","https://openalex.org/W2981393651","https://openalex.org/W3012271043","https://openalex.org/W3012471638","https://openalex.org/W3035442500","https://openalex.org/W3036196915","https://openalex.org/W3095753995","https://openalex.org/W3106763294","https://openalex.org/W3149936330","https://openalex.org/W3173664046","https://openalex.org/W3187816944","https://openalex.org/W3217365746","https://openalex.org/W4286904999","https://openalex.org/W4312473433","https://openalex.org/W4366429755","https://openalex.org/W4383465303","https://openalex.org/W4385245566","https://openalex.org/W4386076204","https://openalex.org/W4390874110"],"related_works":["https://openalex.org/W2158788032","https://openalex.org/W2102546105","https://openalex.org/W2089042722","https://openalex.org/W4281846896","https://openalex.org/W2182037499","https://openalex.org/W1673651863","https://openalex.org/W2052065843","https://openalex.org/W3132103682","https://openalex.org/W2919954508","https://openalex.org/W2142423807"],"abstract_inverted_index":{"Multi-target":[0],"multi-camera":[1,38],"tracking":[2],"(MTMCT),":[3],"focusing":[4],"on":[5,130,162],"inferring":[6],"trajectory":[7],"across":[8],"multiple":[9],"surveillance":[10],"videos,":[11],"is":[12,40],"holding":[13],"significant":[14],"practical":[15],"utility.":[16],"While":[17],"numerous":[18],"studies":[19,161],"aim":[20],"to":[21,26,63,90,144],"learn":[22],"visual":[23,98,141],"features":[24,99],"robust":[25],"illumination":[27],"variation,":[28],"occlusions,":[29],"and":[30,100,159],"other":[31],"issues,":[32],"the":[33,53,65,163,168],"spatio-temporal":[34,49,93,124],"information":[35,50,94,107],"within":[36,108],"a":[37,83,109,118,153],"system":[39],"not":[41],"explored":[42],"sufficiently.":[43],"Existing":[44],"methods":[45],"generally":[46],"exploit":[47],"coarse-grained":[48],"by":[51],"modeling":[52],"distribution":[54],"of":[55,69,106,170],"time":[56],"intervals":[57],"between":[58,127],"cameras.":[59],"However,":[60],"they":[61],"tend":[62],"neglect":[64],"specific":[66],"motion":[67,119,133],"state":[68],"individual":[70],"objects,":[71],"which":[72],"may":[73],"hinder":[74],"accurate":[75],"cross-camera":[76],"association.":[77],"In":[78],"this":[79],"paper,":[80],"we":[81,116],"introduce":[82],"novel":[84],"motionaware":[85],"graph":[86,111,154],"(MAG)":[87],"model":[88],"designed":[89],"extract":[91],"instance-level":[92,132],"that":[95,122],"aligns":[96],"with":[97,140],"seamlessly":[101],"aggregate":[102],"these":[103],"two":[104],"kinds":[105],"unified":[110],"framework":[112],"for":[113,149],"MTMCT.":[114],"Specifically,":[115],"propose":[117],"encoder-decoder":[120],"module":[121],"predicts":[123],"consistency":[125],"scores":[126,136,143],"objects":[128],"based":[129],"their":[131],"states.":[134],"These":[135],"are":[137],"then":[138],"integrated":[139],"similarity":[142],"generate":[145],"discriminative":[146],"feature":[147],"representations":[148],"data":[150],"association":[151],"via":[152],"attention":[155],"mechanism.":[156],"Experimental":[157],"evaluations":[158],"ablation":[160],"large-scale":[164],"MTA":[165],"dataset":[166],"demonstrate":[167],"superiority":[169],"our":[171],"proposed":[172],"model.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
