{"id":"https://openalex.org/W1979246310","doi":"https://doi.org/10.1145/2393347.2393412","title":"Leveraging high-level and low-level features for multimedia event detection","display_name":"Leveraging high-level and low-level features for multimedia event detection","publication_year":2012,"publication_date":"2012-10-29","ids":{"openalex":"https://openalex.org/W1979246310","doi":"https://doi.org/10.1145/2393347.2393412","mag":"1979246310"},"language":"en","primary_location":{"id":"doi:10.1145/2393347.2393412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2393347.2393412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM international conference on Multimedia","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/A5090730336","display_name":"Lu Jiang","orcid":"https://orcid.org/0000-0003-0286-8439"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lu Jiang","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107836252","display_name":"Alexander G. Hauptmann","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander G. Hauptmann","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029285921","display_name":"Guang Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guang Xiang","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA","Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Carnegie-Mellon University, Pittsburgh, Pa., USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090730336"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":9.6092,"has_fulltext":false,"cited_by_count":78,"citation_normalized_percentile":{"value":0.98441395,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"449","last_page":"458"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9990000128746033,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9987000226974487,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.7906190156936646},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6890929937362671},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6459336280822754},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.5714221000671387},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5497184991836548},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.5331363677978516},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4851461350917816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4756740629673004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4455804228782654},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42275387048721313},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.41098737716674805},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37529632449150085},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36113500595092773},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34380805492401123},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12891778349876404},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09535330533981323}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7906190156936646},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6890929937362671},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6459336280822754},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.5714221000671387},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5497184991836548},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.5331363677978516},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4851461350917816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4756740629673004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4455804228782654},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42275387048721313},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.41098737716674805},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37529632449150085},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36113500595092773},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34380805492401123},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12891778349876404},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09535330533981323},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2393347.2393412","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2393347.2393412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM international conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1603881463","https://openalex.org/W1605615716","https://openalex.org/W1989085630","https://openalex.org/W1994203157","https://openalex.org/W2025341678","https://openalex.org/W2041658416","https://openalex.org/W2056952330","https://openalex.org/W2106277773","https://openalex.org/W2119799051","https://openalex.org/W2137253512","https://openalex.org/W2138445151","https://openalex.org/W2145406111","https://openalex.org/W2153959628","https://openalex.org/W2154683974","https://openalex.org/W2162915993","https://openalex.org/W2169177311","https://openalex.org/W2186092502","https://openalex.org/W2483351416","https://openalex.org/W2905522029","https://openalex.org/W4241354775","https://openalex.org/W6679417241","https://openalex.org/W6679740967"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W4247136043","https://openalex.org/W4312407344"],"abstract_inverted_index":{"This":[0],"paper":[1,72],"addresses":[2],"the":[3,25,44,47,52,102,111],"challenge":[4],"of":[5,28,64,133],"Multimedia":[6,117],"Event":[7,118],"Detection":[8,119],"by":[9],"proposing":[10],"a":[11,32,68],"novel":[12],"method":[13,26,104],"for":[14],"high-level":[15,38,69],"and":[16,42,80,85,93,106,110],"low-level":[17,35],"features":[18,39],"fusion":[19],"based":[20],"on":[21,46,114],"collective":[22,87],"classification.":[23],"Generally,":[24],"consists":[27],"three":[29],"steps:":[30],"training":[31],"classifier":[33],"from":[34,60],"features;":[36],"encoding":[37],"into":[40],"graphs;":[41],"diffusing":[43],"scores":[45],"established":[48],"graph":[49,75],"to":[50,67,126],"obtain":[51],"final":[53,56],"prediction.":[54],"The":[55,71,97],"prediction":[57],"is":[58,107],"derived":[59],"multiple":[61],"graphs":[62],"each":[63],"which":[65],"corresponds":[66],"feature.":[70],"investigates":[73],"two":[74,86],"construction":[76],"methods":[77],"using":[78],"logarithmic":[79],"exponential":[81],"loss":[82],"functions,":[83],"respectively":[84],"classification":[88],"algorithms,":[89],"i.e.":[90],"Gibbs":[91],"sampling":[92],"Markov":[94],"random":[95],"walk.":[96],"theoretical":[98],"analysis":[99,113],"demonstrates":[100],"that":[101],"proposed":[103],"converges":[105],"computationally":[108],"scalable":[109],"empirical":[112],"TRECVID":[115],"2011":[116],"dataset":[120],"validates":[121],"its":[122],"outstanding":[123],"performance":[124],"compared":[125],"state-of-the-art":[127],"methods,":[128],"with":[129],"an":[130],"added":[131],"benefit":[132],"interpretability.":[134]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":14},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
