{"id":"https://openalex.org/W1997292542","doi":"https://doi.org/10.1145/2578726.2578742","title":"Multimedia Event Detection Using Hidden Conditional Random Fields","display_name":"Multimedia Event Detection Using Hidden Conditional Random Fields","publication_year":2014,"publication_date":"2014-04-01","ids":{"openalex":"https://openalex.org/W1997292542","doi":"https://doi.org/10.1145/2578726.2578742","mag":"1997292542"},"language":"en","primary_location":{"id":"doi:10.1145/2578726.2578742","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2578726.2578742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of International Conference on Multimedia Retrieval","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/A5013527575","display_name":"Kimiaki Shirahama","orcid":"https://orcid.org/0000-0003-1843-5152"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kimiaki Shirahama","raw_affiliation_strings":["Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen","Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen","institution_ids":["https://openalex.org/I206895457"]},{"raw_affiliation_string":"Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen#TAB#","institution_ids":["https://openalex.org/I206895457"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037990310","display_name":"Marcin Grzegorzek","orcid":"https://orcid.org/0000-0003-4877-8287"},"institutions":[{"id":"https://openalex.org/I206895457","display_name":"University of Siegen","ror":"https://ror.org/02azyry73","country_code":"DE","type":"education","lineage":["https://openalex.org/I206895457"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marcin Grzegorzek","raw_affiliation_strings":["Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen","Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen","institution_ids":["https://openalex.org/I206895457"]},{"raw_affiliation_string":"Research Group for Pattern Recognition, University of Siegen, Germany, Hoelderlinstr. 3, D-57076 Siegen#TAB#","institution_ids":["https://openalex.org/I206895457"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023847482","display_name":"Kuniaki Uehara","orcid":"https://orcid.org/0000-0002-7160-3752"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kuniaki Uehara","raw_affiliation_strings":["Graduate School of System Informatics, Kobe University, Japan, 1-1, Rokkodai, Nada, Kobe 657-8501","Graduate School of System Informatics, Kobe University, Japan, 1-1, Rokkodai, Nada, Kobe 657-8501#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University, Japan, 1-1, Rokkodai, Nada, Kobe 657-8501","institution_ids":["https://openalex.org/I65837984"]},{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University, Japan, 1-1, Rokkodai, Nada, Kobe 657-8501#TAB#","institution_ids":["https://openalex.org/I65837984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9998999834060669,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9986000061035156,"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":0.9976999759674072,"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/conditional-random-field","display_name":"Conditional random field","score":0.9293144941329956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7968562245368958},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7763089537620544},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6208178400993347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.590215802192688},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5587331056594849},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5480020046234131},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5319666266441345},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35682544112205505},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22370877861976624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09996044635772705}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.9293144941329956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7968562245368958},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7763089537620544},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6208178400993347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.590215802192688},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5587331056594849},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5480020046234131},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5319666266441345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35682544112205505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22370877861976624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09996044635772705},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2578726.2578742","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2578726.2578742","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.664.5476","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.664.5476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.pr.informatik.uni-siegen.de/publicationPDFbyID?ID%3D601","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W51979146","https://openalex.org/W53615099","https://openalex.org/W125550756","https://openalex.org/W156236617","https://openalex.org/W1551909886","https://openalex.org/W1607586839","https://openalex.org/W1990190154","https://openalex.org/W2031404913","https://openalex.org/W2042381449","https://openalex.org/W2060940994","https://openalex.org/W2062903088","https://openalex.org/W2089150756","https://openalex.org/W2101534792","https://openalex.org/W2108598243","https://openalex.org/W2112400350","https://openalex.org/W2137117795","https://openalex.org/W2145835757","https://openalex.org/W2147668753","https://openalex.org/W2147880316","https://openalex.org/W2152899661","https://openalex.org/W2156615793","https://openalex.org/W2156772624","https://openalex.org/W2290542723","https://openalex.org/W2341020695","https://openalex.org/W2429638696","https://openalex.org/W4296262844","https://openalex.org/W6611528966","https://openalex.org/W6703525202"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2093471820","https://openalex.org/W2347460059","https://openalex.org/W2111726165","https://openalex.org/W3136048405","https://openalex.org/W182104056","https://openalex.org/W2526939637"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3,14,17,90],"method":[4],"for":[5,13],"Multimedia":[6],"Event":[7],"Detection":[8],"(MED).":[9],"Given":[10],"training":[11,54],"videos":[12,23,55,76,144],"certain":[15],"event,":[16],"classifier":[18],"is":[19,48,65,96],"constructed":[20],"to":[21,106,113,142],"identify":[22],"displaying":[24],"it.":[25],"In":[26,116],"particular,":[27],"the":[28,31,36,51,66,70,114,118,124,128,146,150,161],"problems":[29,130],"of":[30,68,152,163],"weakly":[32],"supervised":[33],"setting":[34],"and":[35,83,110,137],"unclear":[37],"event":[38,71,125,147],"structure":[39,72],"are":[40,131],"addressed":[41],"in":[42,73,165],"this":[43,166],"paper.":[44],"The":[45,62],"first":[46],"issue":[47],"associated":[49],"with":[50],"loosely":[52],"annotated":[53],"that":[56],"usually":[57],"contain":[58],"many":[59],"irrelevant":[60,111],"shots.":[61],"second":[63],"one":[64],"difficulty":[67],"assuming":[69],"advance,":[74],"because":[75],"can":[77],"be":[78],"created":[79],"by":[80,133],"arbitrary":[81],"camera":[82],"editing":[84],"techniques.":[85],"To":[86],"overcome":[87],"these":[88],"problems,":[89],"Hidden":[91],"Conditional":[92],"Random":[93],"Field":[94],"(HCRF)":[95],"used":[97],"where":[98,145],"hidden":[99,121,135],"states":[100,122,136],"work":[101],"as":[102,141],"an":[103],"intermediate":[104],"layer":[105],"discriminate":[107],"between":[108],"relevant":[109],"shots":[112],"event.":[115],"addition,":[117],"relation":[119],"among":[120],"characterises":[123],"structure.":[126],"Thus,":[127],"above":[129],"managed":[132],"optimising":[134],"their":[138],"relation,":[139],"so":[140],"distinguish":[143],"occurs":[148],"from":[149],"rest":[151],"videos.":[153],"Experimental":[154],"results":[155],"on":[156],"TRECVID":[157],"video":[158],"data":[159],"validate":[160],"effectiveness":[162],"HCRFs":[164],"context.":[167]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
