{"id":"https://openalex.org/W2131590007","doi":"https://doi.org/10.1109/iccv.2009.5459427","title":"Selection and context for action recognition","display_name":"Selection and context for action recognition","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2131590007","doi":"https://doi.org/10.1109/iccv.2009.5459427","mag":"2131590007"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2009.5459427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459427","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th 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/A5110632980","display_name":"Dong Seop Han","orcid":"https://orcid.org/0000-0003-4036-950X"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Dong Han","raw_affiliation_strings":["University of Bonn, Germany","University of Bonn. Germany#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"University of Bonn. Germany#TAB#","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085032007","display_name":"Liefeng Bo","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liefeng Bo","raw_affiliation_strings":["TTI-Chicago, USA"],"affiliations":[{"raw_affiliation_string":"TTI-Chicago, USA","institution_ids":["https://openalex.org/I160992636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007658897","display_name":"Cristian Sminchisescu","orcid":"https://orcid.org/0000-0001-5256-886X"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Cristian Sminchisescu","raw_affiliation_strings":["University of Bonn, Germany","University of Bonn. Germany#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"University of Bonn. Germany#TAB#","institution_ids":["https://openalex.org/I135140700"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110632980"],"corresponding_institution_ids":["https://openalex.org/I135140700"],"apc_list":null,"apc_paid":null,"fwci":14.5607,"has_fulltext":false,"cited_by_count":118,"citation_normalized_percentile":{"value":0.99174628,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1933","last_page":"1940"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"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":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7867108583450317},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7676895260810852},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6101860404014587},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5692943334579468},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.5582796931266785},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5358314514160156},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5238766074180603},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5094946026802063},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5093585252761841},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5044153928756714},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.4543740451335907},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.43897730112075806},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.42483580112457275},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.42226359248161316},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.41371607780456543},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4125784635543823},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4108846187591553},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.41023704409599304},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.26126760244369507},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1034039855003357}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7867108583450317},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7676895260810852},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6101860404014587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5692943334579468},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.5582796931266785},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5358314514160156},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5238766074180603},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5094946026802063},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5093585252761841},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5044153928756714},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.4543740451335907},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.43897730112075806},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42483580112457275},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.42226359248161316},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.41371607780456543},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4125784635543823},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4108846187591553},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.41023704409599304},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.26126760244369507},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1034039855003357},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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:10.1109/iccv.2009.5459427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459427","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1517103487","https://openalex.org/W1595717062","https://openalex.org/W1746819321","https://openalex.org/W1984912494","https://openalex.org/W1986517740","https://openalex.org/W2010399676","https://openalex.org/W2024868105","https://openalex.org/W2031823405","https://openalex.org/W2034328688","https://openalex.org/W2077658674","https://openalex.org/W2096691069","https://openalex.org/W2098517267","https://openalex.org/W2103140817","https://openalex.org/W2106833577","https://openalex.org/W2108333036","https://openalex.org/W2111411921","https://openalex.org/W2119799051","https://openalex.org/W2120419212","https://openalex.org/W2126661535","https://openalex.org/W2135658380","https://openalex.org/W2137981002","https://openalex.org/W2140539195","https://openalex.org/W2142194269","https://openalex.org/W2145835757","https://openalex.org/W2151103935","https://openalex.org/W2151214862","https://openalex.org/W2155983176","https://openalex.org/W2156342794","https://openalex.org/W2158169396","https://openalex.org/W2162880125","https://openalex.org/W2163292664","https://openalex.org/W2166761907","https://openalex.org/W2533739470","https://openalex.org/W3012317737","https://openalex.org/W3141200356","https://openalex.org/W4211049957","https://openalex.org/W4212997115","https://openalex.org/W4249279051","https://openalex.org/W6629804754","https://openalex.org/W6635755983","https://openalex.org/W6669838086","https://openalex.org/W6681579763"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W2988126442","https://openalex.org/W1974414866","https://openalex.org/W2057568687","https://openalex.org/W2063982682","https://openalex.org/W2338543196","https://openalex.org/W2963894643"],"abstract_inverted_index":{"Recognizing":[0],"human":[1,87],"action":[2,88,198],"in":[3,43,68,89,130,148,196,207],"non-instrumented":[4,91],"video":[5,58],"is":[6,95],"a":[7,48,115,145,149,159,167,208],"challenging":[8],"task":[9],"not":[10,54],"only":[11,55],"because":[12,30],"of":[13,31,144,161],"the":[14,69,164,175,182,189],"variability":[15],"produced":[16],"by":[17],"general":[18],"scene":[19,77,101],"factors":[20],"like":[21],"illumination,":[22],"background,":[23],"occlusion":[24],"or":[25,38],"intra-class":[26],"variability,":[27],"but":[28,60],"also":[29,61],"subtle":[32],"behavioral":[33],"patterns":[34],"among":[35],"interacting":[36],"people":[37,40,65],"between":[39,64,109],"and":[41,66,79,106,135,141,152,166,203],"objects":[42,67],"images.":[44],"To":[45],"improve":[46],"recognition,":[47],"system":[49],"may":[50],"need":[51],"to":[52,132,186],"use":[53],"low-level":[56,140],"spatio-temporal":[57],"correlations":[59],"relational":[62],"descriptors":[63,78,102,202],"scene.":[70],"In":[71],"this":[72],"paper":[73],"we":[74,98,113,178,192],"present":[75],"contextual":[76],"Bayesian":[80,117],"multiple":[81,125,137],"kernel":[82,126],"learning":[83],"methods":[84],"for":[85],"recognizing":[86],"complex":[90],"video.":[92],"Our":[93],"contribution":[94],"threefold:":[96],"(1)":[97],"introduce":[99],"bag-of-detector":[100],"that":[103],"encode":[104],"presence/absence":[105],"structural":[107],"relations":[108],"object":[110],"parts;":[111],"(2)":[112],"derive":[114],"novel":[116],"classification":[118],"method":[119],"based":[120],"on":[121,163],"Gaussian":[122],"processes":[123],"with":[124],"covariance":[127],"functions":[128],"(MKGPC),":[129],"order":[131],"automatically":[133],"select":[134],"weight":[136],"features,":[138],"both":[139],"high-level,":[142],"out":[143],"large":[146,155],"collection,":[147],"principled":[150],"way,":[151],"(3)":[153],"perform":[154],"scale":[156],"evaluation":[157],"using":[158,200],"variety":[160],"features":[162],"KTH":[165,176],"recently":[168],"introduced,":[169],"challenging,":[170],"Hollywood":[171,190],"movie":[172],"dataset.":[173],"On":[174,188],"dataset,":[177],"obtain":[179,193],"94.1%":[180],"accuracy,":[181],"best":[183],"result":[184],"reported":[185],"date.":[187],"dataset":[191],"promising":[194],"results":[195],"several":[197],"classes":[199],"fewer":[201],"about":[204],"9.1%":[205],"improvement":[206],"previous":[209],"benchmark":[210],"test.":[211]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":16},{"year":2013,"cited_by_count":18},{"year":2012,"cited_by_count":18}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
