{"id":"https://openalex.org/W2015461918","doi":"https://doi.org/10.1109/iccv.2011.6126525","title":"Video parsing for abnormality detection","display_name":"Video parsing for abnormality detection","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2015461918","doi":"https://doi.org/10.1109/iccv.2011.6126525","mag":"2015461918"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2011.6126525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","raw_type":"proceedings-article"},"type":"article","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/A5029772771","display_name":"Borislav Anti\u0107","orcid":null},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Borislav Antic","raw_affiliation_strings":["Interdisciplinary Center of Scientific Computing, University of Heidelberg, Germany","Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Interdisciplinary Center of Scientific Computing, University of Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]},{"raw_affiliation_string":"Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084415727","display_name":"Bj\u00f6rn Ommer","orcid":"https://orcid.org/0000-0003-0766-120X"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bjorn Ommer","raw_affiliation_strings":["Interdisciplinary Center of Scientific Computing, University of Heidelberg, Germany","Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Interdisciplinary Center of Scientific Computing, University of Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]},{"raw_affiliation_string":"Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.474,"has_fulltext":false,"cited_by_count":166,"citation_normalized_percentile":{"value":0.9704483,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2415","last_page":"2422"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9954000115394592,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9811999797821045,"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/abnormality","display_name":"Abnormality","score":0.9228936433792114},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7446081042289734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6778215169906616},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6236430406570435},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.5723602771759033},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5692955255508423},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5420895218849182},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49967360496520996},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4925399720668793},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.48809778690338135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38234660029411316},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3234844505786896},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07067346572875977}],"concepts":[{"id":"https://openalex.org/C50965678","wikidata":"https://www.wikidata.org/wiki/Q2724302","display_name":"Abnormality","level":2,"score":0.9228936433792114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7446081042289734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6778215169906616},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6236430406570435},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.5723602771759033},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5692955255508423},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5420895218849182},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49967360496520996},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4925399720668793},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.48809778690338135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38234660029411316},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3234844505786896},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07067346572875977},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv.2011.6126525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1866030367","https://openalex.org/W2034328688","https://openalex.org/W2056860348","https://openalex.org/W2087515439","https://openalex.org/W2107448204","https://openalex.org/W2109389234","https://openalex.org/W2110140398","https://openalex.org/W2122361470","https://openalex.org/W2124658620","https://openalex.org/W2125849446","https://openalex.org/W2127923214","https://openalex.org/W2131628350","https://openalex.org/W2134261358","https://openalex.org/W2138092272","https://openalex.org/W2140435402","https://openalex.org/W2142412278","https://openalex.org/W2145743319","https://openalex.org/W2149021215","https://openalex.org/W2151103935","https://openalex.org/W2153635508","https://openalex.org/W2154086615","https://openalex.org/W2161017465","https://openalex.org/W2163147152","https://openalex.org/W2164261375","https://openalex.org/W2164489414","https://openalex.org/W2169536486","https://openalex.org/W2539222059","https://openalex.org/W2539525772","https://openalex.org/W4249279051","https://openalex.org/W4285719527","https://openalex.org/W6639201943","https://openalex.org/W6657123155","https://openalex.org/W6678684981","https://openalex.org/W6678780061","https://openalex.org/W6680382358","https://openalex.org/W6680470121","https://openalex.org/W6728706464"],"related_works":["https://openalex.org/W2502722637","https://openalex.org/W1564661574","https://openalex.org/W3044272884","https://openalex.org/W2799803467","https://openalex.org/W2614183994","https://openalex.org/W3201070945","https://openalex.org/W2753840555","https://openalex.org/W4206233339","https://openalex.org/W3133521594","https://openalex.org/W2792951589"],"abstract_inverted_index":{"Detecting":[0],"abnormalities":[1,39,163],"in":[2,72],"video":[3,96],"is":[4,17,36,75],"a":[5,33,100,128,158,181],"challenging":[6,169],"problem":[7,93],"since":[8],"the":[9,58,69,108,122,145,168,175,189],"class":[10],"of":[11,88,102,131,171,186],"all":[12,107],"irregular":[13],"objects":[14],"and":[15,19,188],"behaviors":[16],"infinite":[18],"thus":[20],"no":[21],"(or":[22],"by":[23,98,151,177,193],"far":[24],"not":[25,49,62],"enough)":[26],"abnormal":[27,52,81],"training":[28,59,118],"samples":[29,119,153],"are":[30,45,134,141],"available.":[31],"Consequently,":[32,124],"standard":[34],"setting":[35],"to":[37,76,115,179,195],"find":[38,116],"without":[40,147],"actually":[41],"knowing":[42],"what":[43,64],"they":[44],"because":[46],"we":[47,94,125],"have":[48],"been":[50],"shown":[51],"examples":[53],"during":[54],"training.":[55],"However,":[56],"although":[57],"data":[60],"does":[61],"define":[63],"an":[65,149],"abnormality":[66,183],"looks":[67],"like,":[68],"main":[70],"paradigm":[71],"this":[73,92],"field":[74],"directly":[77],"search":[78],"for":[79,143,154],"individual":[80],"local":[82],"patches":[83],"or":[84],"image":[85],"regions":[86],"independent":[87],"another.":[89],"To":[90],"address":[91],"parse":[95],"frames":[97],"establishing":[99],"set":[101],"hypotheses":[103,139],"that":[104,120,161],"jointly":[105],"explain":[106,121],"foreground":[109,146],"while,":[110],"at":[111],"same":[112],"time,":[113],"trying":[114],"normal":[117,152],"hypotheses.":[123],"can":[126],"avoid":[127],"direct":[129],"detection":[130],"abnormalities.":[132],"They":[133],"discovered":[135],"indirectly":[136],"as":[137],"those":[138],"which":[140],"needed":[142],"covering":[144],"finding":[148],"explanation":[150],"themselves.":[155],"We":[156],"present":[157],"probabilistic":[159],"model":[160],"localizes":[162],"using":[164],"statistical":[165],"inference.":[166],"On":[167],"dataset":[170],"[15]":[172],"it":[173],"outperforms":[174],"state-of-the-art":[176],"7%":[178],"achieve":[180],"frame-based":[182],"classification":[184],"performance":[185,191],"91%":[187],"localization":[190],"improves":[192],"32%":[194],"76%.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":19},{"year":2015,"cited_by_count":12},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":9}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
