{"id":"https://openalex.org/W2100916003","doi":"https://doi.org/10.1109/cvpr.2009.5206744","title":"Recognizing realistic actions from videos \u201cin the wild\u201d","display_name":"Recognizing realistic actions from videos \u201cin the wild\u201d","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2100916003","doi":"https://doi.org/10.1109/cvpr.2009.5206744","mag":"2100916003"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206744","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://stars.library.ucf.edu/scopus2000/12718","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032552506","display_name":"Jingen Liu","orcid":"https://orcid.org/0000-0003-3133-3644"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jingen Liu","raw_affiliation_strings":["Computer Vision Laboratory, University of Central Florida, USA","Comput. Vision Lab., Univ. of Central Florida, Orlando, FL, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Comput. Vision Lab., Univ. of Central Florida, Orlando, FL, USA#TAB#","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055469774","display_name":"Jiebo Luo","orcid":"https://orcid.org/0000-0002-4516-9729"},"institutions":[{"id":"https://openalex.org/I4210094723","display_name":"Kodak (Japan)","ror":"https://ror.org/00tee0349","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210094723","https://openalex.org/I4210159451"]},{"id":"https://openalex.org/I4210159451","display_name":"Kodak (United States)","ror":"https://ror.org/04rn3ph18","country_code":"US","type":"company","lineage":["https://openalex.org/I4210159451"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Jiebo Luo","raw_affiliation_strings":["Kodak Research Laboratories, Eastman Kodak (Japan) Limited, USA","Kodak Res. Labs., Eastman Kodak Co., Rochester, NY, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Kodak Research Laboratories, Eastman Kodak (Japan) Limited, USA","institution_ids":["https://openalex.org/I4210094723"]},{"raw_affiliation_string":"Kodak Res. Labs., Eastman Kodak Co., Rochester, NY, USA#TAB#","institution_ids":["https://openalex.org/I4210159451"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080823547","display_name":"Mubarak Shah","orcid":"https://orcid.org/0000-0001-6172-5572"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mubarak Shah","raw_affiliation_strings":["Computer Vision Laboratory, University of Central Florida, USA","Comput. Vision Lab., Univ. of Central Florida, Orlando, FL, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Comput. Vision Lab., Univ. of Central Florida, Orlando, FL, USA#TAB#","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032552506"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":27.3711,"has_fulltext":false,"cited_by_count":1085,"citation_normalized_percentile":{"value":0.99760622,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1996","last_page":"2003"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9984999895095825,"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":0.8170417547225952},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7884947657585144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7084720730781555},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5646454691886902},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49894261360168457},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.4904610812664032},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.48650211095809937},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.46658140420913696},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44716840982437134},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4282805919647217},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4217844009399414},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4212597608566284},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41493287682533264},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.41233834624290466},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.25441181659698486},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.241031676530838}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8170417547225952},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7884947657585144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7084720730781555},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5646454691886902},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49894261360168457},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4904610812664032},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.48650211095809937},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.46658140420913696},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44716840982437134},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4282805919647217},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4217844009399414},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4212597608566284},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41493287682533264},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.41233834624290466},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25441181659698486},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.241031676530838},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2009.5206744","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206744","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:stars.library.ucf.edu:scopus2000-13717","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2000/12718","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2000s","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.152.8982","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.152.8982","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://longwood.cs.ucf.edu/~vision/papers/cvpr2009/cvpr2009_liu1.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:stars.library.ucf.edu:scopus2000-13717","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2000/12718","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2000s","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1526529273","https://openalex.org/W1572333066","https://openalex.org/W1966280301","https://openalex.org/W1980911747","https://openalex.org/W2021733262","https://openalex.org/W2066636486","https://openalex.org/W2103658758","https://openalex.org/W2110142955","https://openalex.org/W2119479037","https://openalex.org/W2119799051","https://openalex.org/W2129418188","https://openalex.org/W2135735112","https://openalex.org/W2138570191","https://openalex.org/W2140363548","https://openalex.org/W2142194269","https://openalex.org/W2146776177","https://openalex.org/W2148293470","https://openalex.org/W2148948295","https://openalex.org/W2149126415","https://openalex.org/W2151259137","https://openalex.org/W2151768982","https://openalex.org/W2163273012","https://openalex.org/W2165095705","https://openalex.org/W2166070055","https://openalex.org/W2166820607","https://openalex.org/W2167970616","https://openalex.org/W2533739470","https://openalex.org/W4205885661","https://openalex.org/W4285719527","https://openalex.org/W6675276727","https://openalex.org/W6679000042","https://openalex.org/W6680786152","https://openalex.org/W6682071048","https://openalex.org/W6682450948","https://openalex.org/W6682464122","https://openalex.org/W6684886437"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W1981531423"],"abstract_inverted_index":{"In":[0,128],"this":[1],"paper,":[2],"we":[3,97],"present":[4],"a":[5,138],"systematic":[6],"framework":[7,167],"for":[8,161,193],"recognizing":[9],"realistic":[10],"actions":[11,181],"from":[12,33,49,72,83,183],"videos":[13,19,35],"\u201cin":[14],"the":[15,29,44,73,84,87,123,156,166,169],"wild.\u201d":[16],"Such":[17],"unconstrained":[18,74],"are":[20,93],"abundant":[21],"in":[22,55],"personal":[23,186],"collections":[24],"as":[25,27],"well":[26],"on":[28,168],"web.":[30],"Recognizing":[31],"action":[32,194,197],"such":[34],"has":[36],"not":[37],"been":[38],"addressed":[39],"extensively,":[40],"primarily":[41],"due":[42],"to":[43,66,100,108,121,130,144,153],"tremendous":[45],"variations":[46],"that":[47],"result":[48],"camera":[50],"motion,":[51],"background":[52],"clutter,":[53],"changes":[54],"object":[56],"appearance,":[57],"and":[58,69,80,113,172,185,188,196],"scale,":[59],"etc.":[60],"The":[61],"main":[62],"challenge":[63],"is":[64,119,142,151],"how":[65],"extract":[67,77],"reliable":[68],"informative":[70,125],"features":[71,82,89,112,160],"videos.":[75,85],"We":[76,104,163],"both":[78,91],"motion":[79,106,111],"static":[81,115,126],"Since":[86],"raw":[88],"of":[90,177,180],"types":[92],"dense":[94],"yet":[95,134,158],"noisy,":[96],"propose":[98],"strategies":[99],"prune":[101],"these":[102],"features.":[103,116,127,148],"use":[105],"statistics":[107],"acquire":[109],"stable":[110],"clean":[114],"Furthermore,":[117],"PageRank":[118],"used":[120],"mine":[122],"most":[124],"order":[129],"further":[131],"construct":[132],"compact":[133],"discriminative":[135],"visual":[136],"vocabularies,":[137],"divisive":[139],"information-theoretic":[140],"algorithm":[141],"employed":[143],"group":[145],"semantically":[146],"related":[147],"Finally,":[149],"AdaBoost":[150],"chosen":[152],"integrate":[154],"all":[155],"heterogeneous":[157],"complementary":[159],"recognition.":[162],"have":[164,189],"tested":[165],"KTH":[170],"dataset":[171,175],"our":[173],"own":[174],"consisting":[176],"11":[178],"categories":[179],"collected":[182],"YouTube":[184],"videos,":[187],"obtained":[190],"impressive":[191],"results":[192],"recognition":[195],"localization.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":40},{"year":2022,"cited_by_count":37},{"year":2021,"cited_by_count":63},{"year":2020,"cited_by_count":63},{"year":2019,"cited_by_count":55},{"year":2018,"cited_by_count":55},{"year":2017,"cited_by_count":77},{"year":2016,"cited_by_count":98},{"year":2015,"cited_by_count":94},{"year":2014,"cited_by_count":124},{"year":2013,"cited_by_count":108},{"year":2012,"cited_by_count":100}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
