{"id":"https://openalex.org/W4385568279","doi":"https://doi.org/10.1145/3580305.3599952","title":"SAInf: Stay Area Inference of Vehicles using Surveillance Camera Records","display_name":"SAInf: Stay Area Inference of Vehicles using Surveillance Camera Records","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385568279","doi":"https://doi.org/10.1145/3580305.3599952"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599952","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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/A5071182342","display_name":"Zhipeng Ma","orcid":"https://orcid.org/0009-0008-1485-0766"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Ma","raw_affiliation_strings":["Southwest Jiaotong University &amp; JD iCity, JD Technology, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0008-1485-0766","affiliations":[{"raw_affiliation_string":"Southwest Jiaotong University &amp; JD iCity, JD Technology, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013846634","display_name":"Chuishi Meng","orcid":"https://orcid.org/0000-0002-1995-5291"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuishi Meng","raw_affiliation_strings":["JD iCity, JD Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1995-5291","affiliations":[{"raw_affiliation_string":"JD iCity, JD Technology, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103090461","display_name":"Huimin Ren","orcid":"https://orcid.org/0000-0003-3822-3288"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huimin Ren","raw_affiliation_strings":["JD iCity, JD Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3822-3288","affiliations":[{"raw_affiliation_string":"JD iCity, JD Technology, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006117974","display_name":"Sijie Ruan","orcid":"https://orcid.org/0000-0002-4520-7174"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sijie Ruan","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4520-7174","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081699807","display_name":"Jie Bao","orcid":"https://orcid.org/0000-0002-7011-990X"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Bao","raw_affiliation_strings":["JD iCity, JD Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7011-990X","affiliations":[{"raw_affiliation_string":"JD iCity, JD Technology, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080111310","display_name":"Xiaoting Wang","orcid":"https://orcid.org/0000-0003-2135-8389"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoting Wang","raw_affiliation_strings":["JD iCity, JD Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2135-8389","affiliations":[{"raw_affiliation_string":"JD iCity, JD Technology, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070559820","display_name":"Tianrui Li","orcid":"https://orcid.org/0000-0001-7780-104X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Li","raw_affiliation_strings":["Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-7780-104X","affiliations":[{"raw_affiliation_string":"Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016698883","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0003-2537-4685"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["JD iCity, JD Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2537-4685","affiliations":[{"raw_affiliation_string":"JD iCity, JD Technology, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":null,"issue":null,"first_page":"4595","last_page":"4604"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980000257492065,"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/T11106","display_name":"Data Management and Algorithms","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8261508941650391},{"id":"https://openalex.org/keywords/traverse","display_name":"Traverse","score":0.8189839124679565},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.7103602886199951},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6676796674728394},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6315479278564453},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5767433643341064},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5268382430076599},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.46228766441345215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4075261354446411},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.350881963968277},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35006827116012573},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15331333875656128},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09843483567237854},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.08251911401748657}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8261508941650391},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.8189839124679565},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.7103602886199951},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6676796674728394},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6315479278564453},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5767433643341064},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5268382430076599},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.46228766441345215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4075261354446411},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.350881963968277},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35006827116012573},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15331333875656128},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09843483567237854},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08251911401748657},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599952","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599952","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8199999928474426,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G365603399","display_name":null,"funder_award_id":"Z211100002121112","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"},{"id":"https://openalex.org/G4115684213","display_name":null,"funder_award_id":"62176221","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4363312152","display_name":null,"funder_award_id":"2019YFB2103201","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8602430720","display_name":null,"funder_award_id":"6120220113","funder_id":"https://openalex.org/F4320327514","funder_display_name":"Beijing Institute of Technology Research Fund Program for Young Scholars"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323110","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74"},{"id":"https://openalex.org/F4320327514","display_name":"Beijing Institute of Technology Research Fund Program for Young Scholars","ror":null},{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W591024134","https://openalex.org/W1561934083","https://openalex.org/W1966144751","https://openalex.org/W1998250073","https://openalex.org/W2065663378","https://openalex.org/W2070868259","https://openalex.org/W2075190119","https://openalex.org/W2080721274","https://openalex.org/W2112738128","https://openalex.org/W2126194848","https://openalex.org/W2149058896","https://openalex.org/W2154851992","https://openalex.org/W2194775991","https://openalex.org/W2547992514","https://openalex.org/W2797583062","https://openalex.org/W2809035759","https://openalex.org/W2809079004","https://openalex.org/W2810586154","https://openalex.org/W2904813135","https://openalex.org/W2908054697","https://openalex.org/W2948104333","https://openalex.org/W2967385518","https://openalex.org/W2976507065","https://openalex.org/W3011902235","https://openalex.org/W3080707569","https://openalex.org/W3104097132","https://openalex.org/W3147042931","https://openalex.org/W3196509900","https://openalex.org/W3213458765","https://openalex.org/W3214005682","https://openalex.org/W4206720847","https://openalex.org/W4221058158","https://openalex.org/W4290944872"],"related_works":["https://openalex.org/W2377402383","https://openalex.org/W2380835401","https://openalex.org/W2381912691","https://openalex.org/W2350381577","https://openalex.org/W2353618196","https://openalex.org/W2348074676","https://openalex.org/W2385033175","https://openalex.org/W2374043190","https://openalex.org/W2363298784","https://openalex.org/W2367402697"],"abstract_inverted_index":{"Stay":[0],"area":[1,24,122,145,168],"detection":[2,25,123,146],"is":[3,15,97],"one":[4],"of":[5,39,70,189],"the":[6,75,90,101,120,129,143,154,173,187,190,195],"most":[7,49],"important":[8,108],"applications":[9],"in":[10,48,60,85,94,107],"trajectory":[11,91,115],"data":[12,31,44,92,182],"mining,":[13],"which":[14],"helpful":[16],"to":[17,141,171,185],"understand":[18],"human's":[19],"behavior":[20],"intentions.":[21],"Traditional":[22],"stay":[23,121,130,144,155,167,175],"methods":[26],"are":[27,104],"based":[28,179],"on":[29,180],"GPS":[30,43],"with":[32,148,205],"relatively":[33],"high":[34],"sampling":[35],"rate.":[36],"However,":[37,89],"because":[38,100],"privacy":[40],"issues,":[41],"accessing":[42],"can":[45,80],"be":[46,81],"difficult":[47],"real-world":[50,181],"applications.":[51],"Fortunately,":[52],"traffic":[53],"surveillance":[54,102,159],"cameras":[55,103],"have":[56],"been":[57],"widely":[58],"deployed":[59,106],"urban":[61],"area,":[62],"and":[63,83,127],"it":[64],"provides":[65],"us":[66],"a":[67,86,138,158,165,200],"novel":[68],"way":[69,96],"acquiring":[71],"vehicles'":[72],"trajectories.":[73,150],"All":[74],"vehicles":[76],"that":[77],"traverse":[78],"by":[79],"recognized":[82],"recorded":[84],"passive":[87],"way.":[88],"collected":[93],"this":[95,134],"extremely":[98],"coarse,":[99],"only":[105],"locations,":[109],"such":[110],"as":[111],"crossroads.":[112],"This":[113],"coarse":[114,149],"introduces":[116],"two":[117],"challenges":[118],"for":[119],"problem,":[124],"i.e.,":[125],"whether":[126],"where":[128],"event":[131,156],"occurs.":[132],"In":[133],"paper,":[135],"we":[136],"design":[137],"two-stage":[139],"method":[140],"solve":[142],"problem":[147],"It":[151],"first":[152],"detects":[153],"between":[157],"camera":[160],"record":[161],"pair,":[162],"then":[163],"uses":[164],"layer-by-layer":[166],"identification":[169],"algorithm":[170],"infer":[172],"exact":[174],"area.":[176],"Extensive":[177],"experiments":[178],"were":[183],"used":[184],"evaluate":[186],"performance":[188,202],"proposed":[191,196],"framework.":[192],"Results":[193],"demonstrate":[194],"framework":[197],"SAInf":[198],"achieved":[199],"58%":[201],"improvement":[203],"compared":[204],"SOTA":[206],"methods.":[207]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
