{"id":"https://openalex.org/W2968202956","doi":"https://doi.org/10.1109/wacv45572.2020.9093633","title":"Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection","display_name":"Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W2968202956","doi":"https://doi.org/10.1109/wacv45572.2020.9093633","mag":"2968202956"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093633","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1908.04321","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075227880","display_name":"Royston Rodrigues","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Royston Rodrigues","raw_affiliation_strings":["NEC Corporation, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Corporation, Japan","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025512806","display_name":"Neha Bhargava","orcid":null},"institutions":[{"id":"https://openalex.org/I124261462","display_name":"Oxford Brookes University","ror":"https://ror.org/04v2twj65","country_code":"GB","type":"education","lineage":["https://openalex.org/I124261462"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Neha Bhargava","raw_affiliation_strings":["Oxford Brookes University","(Oxford Brookes University)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Oxford Brookes University","institution_ids":["https://openalex.org/I124261462"]},{"raw_affiliation_string":"(Oxford Brookes University)","institution_ids":["https://openalex.org/I124261462"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103090020","display_name":"Rajbabu Velmurugan","orcid":"https://orcid.org/0000-0002-3511-1806"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajbabu Velmurugan","raw_affiliation_strings":["Indian Institute of Technology Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016405213","display_name":"Subhasis Chaudhuri","orcid":"https://orcid.org/0000-0002-1680-0016"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subhasis Chaudhuri","raw_affiliation_strings":["Indian Institute of Technology Bombay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4062,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67940566,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2615","last_page":"2623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9991000294685364,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9973000288009644,"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/trajectory","display_name":"Trajectory","score":0.7490689158439636},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7384411096572876},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7099094390869141},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6662302613258362},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.637742280960083},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5943698287010193},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5464845299720764},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.5264107584953308},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5067968964576721},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4892098903656006},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.47999852895736694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4630560576915741},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36153358221054077},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07854783535003662},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06356707215309143}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7490689158439636},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7384411096572876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099094390869141},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6662302613258362},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.637742280960083},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5943698287010193},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5464845299720764},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.5264107584953308},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5067968964576721},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4892098903656006},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.47999852895736694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4630560576915741},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36153358221054077},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07854783535003662},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06356707215309143},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093633","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1908.04321","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.04321","pdf_url":"https://arxiv.org/pdf/1908.04321","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2968202956","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1908.04321","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1908.04321","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1908.04321","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1908.04321","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.04321","pdf_url":"https://arxiv.org/pdf/1908.04321","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2968202956.pdf","grobid_xml":"https://content.openalex.org/works/W2968202956.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1967456674","https://openalex.org/W2163612318","https://openalex.org/W2164261375","https://openalex.org/W2194550927","https://openalex.org/W2341058432","https://openalex.org/W2557728737","https://openalex.org/W2559085405","https://openalex.org/W2777288981","https://openalex.org/W2777342313","https://openalex.org/W2889935068","https://openalex.org/W2921906393","https://openalex.org/W2925312408","https://openalex.org/W2962730651","https://openalex.org/W2962791923","https://openalex.org/W2963011882","https://openalex.org/W2963240734","https://openalex.org/W2963610939","https://openalex.org/W2963795951","https://openalex.org/W2963899855","https://openalex.org/W2964232409","https://openalex.org/W3099887740","https://openalex.org/W6642206748"],"related_works":["https://openalex.org/W3214661750","https://openalex.org/W2897307920","https://openalex.org/W2157135189","https://openalex.org/W2868855294","https://openalex.org/W2979879363","https://openalex.org/W159393891","https://openalex.org/W3035726468","https://openalex.org/W2073469005","https://openalex.org/W2918145993","https://openalex.org/W3118599319","https://openalex.org/W2951373802","https://openalex.org/W2797454564","https://openalex.org/W3100854855","https://openalex.org/W1952828156","https://openalex.org/W2773053298","https://openalex.org/W3171634830","https://openalex.org/W2899789547","https://openalex.org/W2589040423","https://openalex.org/W2096126430","https://openalex.org/W3097257806"],"abstract_inverted_index":{"A":[0,85],"classical":[1],"approach":[2,37],"to":[3,8,25,93,113,149,153,160],"abnormal":[4,27,60,162,171],"activity":[5,172],"detection":[6],"is":[7,71,77,90,142],"learn":[9],"a":[10,40,45,51,72,78,82,110,135,169],"representation":[11,24],"for":[12,134,174],"normal":[13],"activities":[14,28,61],"from":[15],"the":[16,32,95,115,123,186,191],"training":[17],"data":[18],"and":[19,75,87,128,197],"then":[20],"use":[21,176],"this":[22,36,106],"learned":[23],"detect":[26,161],"while":[29],"testing.":[30],"Typically,":[31],"methods":[33],"based":[34],"on":[35],"operate":[38],"at":[39,65,118,131],"fixed":[41],"timescale":[42,89],"-":[43],"either":[44],"single":[46,86],"time-instant":[47],"(e.g.":[48,55],"frame-based)":[49],"or":[50],"constant":[52],"time":[53,103,195],"duration":[54,196],"video-clip":[56],"based).":[57],"But":[58],"human":[59],"can":[62,189],"take":[63],"place":[64],"different":[66,102,119,132,154,194],"timescales.":[67,120,155],"For":[68],"example,":[69],"jumping":[70],"short-term":[73],"anomaly":[74,80],"loitering":[76],"long-term":[79],"in":[81],"surveillance":[83],"scenario.":[84],"pre-defined":[88],"not":[91],"enough":[92],"capture":[94,114,190],"wide":[96],"range":[97],"of":[98,193],"anomalies":[99,192],"occurring":[100],"with":[101],"duration.":[104],"In":[105,121,164],"paper,":[107],"we":[108,166],"propose":[109],"multi-timescale":[111],"model":[112,125,141,188],"temporal":[116],"dynamics":[117],"particular,":[122],"proposed":[124,187],"makes":[126],"future":[127],"past":[129],"predictions":[130,151,157],"timescales":[133],"given":[136],"input":[137],"pose":[138],"trajectory.":[139],"The":[140],"multi-layered":[143],"where":[144],"intermediate":[145],"layers":[146],"are":[147,158],"responsible":[148],"generate":[150],"corresponding":[152],"These":[156],"combined":[159],"activities.":[163],"addition,":[165],"also":[167],"introduce":[168],"single-camera":[170],"dataset":[173],"research":[175],"that":[177,185],"contains":[178],"483,566":[179],"annotated":[180],"frames.":[181],"Our":[182],"experiments":[183],"show":[184],"outperforms":[198],"existing":[199],"methods.":[200]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
