{"id":"https://openalex.org/W2076666921","doi":"https://doi.org/10.1109/avss.2014.6918655","title":"Abnormal event detection using local sparse representation","display_name":"Abnormal event detection using local sparse representation","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2076666921","doi":"https://doi.org/10.1109/avss.2014.6918655","mag":"2076666921"},"language":"en","primary_location":{"id":"doi:10.1109/avss.2014.6918655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2014.6918655","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","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/A5024226356","display_name":"Huamin Ren","orcid":"https://orcid.org/0000-0003-3554-596X"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Huamin Ren","raw_affiliation_strings":["Visual Analysis of People Laboratory, Aalborg University, Denmark","Visual Analysis of People laboratory, Aalborg University, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Visual Analysis of People Laboratory, Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]},{"raw_affiliation_string":"Visual Analysis of People laboratory, Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022176859","display_name":"Thomas B. Moeslund","orcid":"https://orcid.org/0000-0001-7584-5209"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Thomas B. Moeslund","raw_affiliation_strings":["Visual Analysis of People Laboratory, Aalborg University, Denmark","Visual Analysis of People laboratory, Aalborg University, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Visual Analysis of People Laboratory, Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]},{"raw_affiliation_string":"Visual Analysis of People laboratory, Aalborg University, Denmark","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I891191580"],"apc_list":null,"apc_paid":null,"fwci":1.2406,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.81600531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9678999781608582,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/abnormality","display_name":"Abnormality","score":0.7675117254257202},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7030541300773621},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6967012286186218},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6554964780807495},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6483193635940552},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5954387784004211},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.575417697429657},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.544931948184967},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5438616275787354},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5148083567619324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48890963196754456},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.48736339807510376},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4695585072040558},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4195815324783325},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33628636598587036}],"concepts":[{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.7675117254257202},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7030541300773621},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6967012286186218},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6554964780807495},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6483193635940552},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5954387784004211},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.575417697429657},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.544931948184967},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5438616275787354},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5148083567619324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48890963196754456},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.48736339807510376},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4695585072040558},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4195815324783325},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33628636598587036},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/avss.2014.6918655","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2014.6918655","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/54935ccf-da99-451d-bd50-35d783e341c5","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/54935ccf-da99-451d-bd50-35d783e341c5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Ren , H &amp; Moeslund , T B 2014 , Abnormal Event Detection Using Local Sparse Representation . in 2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) . IEEE Computer Society Press , pp. 125-130 , AVSS 2014 , Seoul , Korea, Republic of , 26/08/2014 . https://doi.org/10.1109/AVSS.2014.6918655","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W8251247","https://openalex.org/W1993962865","https://openalex.org/W2003217181","https://openalex.org/W2012931101","https://openalex.org/W2021659075","https://openalex.org/W2030449718","https://openalex.org/W2105464873","https://openalex.org/W2110383222","https://openalex.org/W2122361470","https://openalex.org/W2125105611","https://openalex.org/W2138092272","https://openalex.org/W2147276092","https://openalex.org/W2163612318","https://openalex.org/W2164261375","https://openalex.org/W2164931791","https://openalex.org/W2165874743","https://openalex.org/W2986028972","https://openalex.org/W4247760752","https://openalex.org/W6658096495","https://openalex.org/W6680470121","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W4247543202","https://openalex.org/W1980381208","https://openalex.org/W4243456421","https://openalex.org/W4240842027","https://openalex.org/W2417397217","https://openalex.org/W2364594919","https://openalex.org/W2167092671","https://openalex.org/W2258058088","https://openalex.org/W1826223126","https://openalex.org/W2158511632"],"abstract_inverted_index":{"We":[0,106],"propose":[1,39],"to":[2,76,122],"detect":[3,23],"abnormal":[4,82,88],"events":[5],"via":[6],"a":[7,57,78],"sparse":[8],"subspace":[9],"clustering":[10],"algorithm.":[11],"Unlike":[12],"most":[13],"existing":[14],"approaches,":[15],"which":[16],"search":[17],"for":[18,67],"optimized":[19],"normal":[20,36,49,59,102],"bases":[21,60],"and":[22,51,100,116],"abnormality":[24,41],"based":[25,43],"on":[26,44,110],"least":[27],"square":[28],"error":[29,32],"or":[30],"reconstruction":[31],"from":[33],"the":[34,45,48,94,101,123],"learned":[35],"patterns,":[37],"we":[38,55,71],"an":[40],"measurement":[42],"difference":[46],"between":[47,96],"space":[50,99,103],"local":[52,79,98],"space.":[53,80],"Specifically,":[54],"provide":[56],"reasonable":[58],"through":[61],"repeated":[62],"K":[63],"spectral":[64],"clustering.":[65],"Then":[66],"each":[68],"testing":[69],"feature":[70,89],"first":[72],"use":[73],"temporal":[74],"neighbors":[75],"form":[77],"An":[81],"event":[83],"is":[84,90,104],"found":[85,91],"if":[86],"any":[87],"that":[92],"satisfies:":[93],"distance":[95],"its":[97],"large.":[105],"evaluate":[107],"our":[108,127],"method":[109],"two":[111],"public":[112],"benchmark":[113],"datasets:":[114],"UCSD":[115],"Subway":[117],"Entrance":[118],"datasets.":[119],"The":[120],"comparison":[121],"state-of-the-art":[124],"methods":[125],"validate":[126],"method's":[128],"effectiveness.":[129]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
