{"id":"https://openalex.org/W2499974702","doi":"https://doi.org/10.1145/2962719","title":"Semantic Feature Mining for Video Event Understanding","display_name":"Semantic Feature Mining for Video Event Understanding","publication_year":2016,"publication_date":"2016-08-03","ids":{"openalex":"https://openalex.org/W2499974702","doi":"https://doi.org/10.1145/2962719","mag":"2499974702"},"language":"en","primary_location":{"id":"doi:10.1145/2962719","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2962719","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-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/A5083991825","display_name":"Xiaoshan Yang","orcid":"https://orcid.org/0000-0001-5453-9755"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoshan Yang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648981","display_name":"Tianzhu Zhang","orcid":"https://orcid.org/0000-0003-1856-9564"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianzhu Zhang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083991825"],"corresponding_institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":1.50464146,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88945488,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"12","issue":"4","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","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/T10812","display_name":"Human Pose and Action Recognition","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/T11439","display_name":"Video Analysis and Summarization","score":0.9995999932289124,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9988999962806702,"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":0.8489614725112915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6745094060897827},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6665862202644348},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6499588489532471},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6095523238182068},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.5837236642837524},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5632838606834412},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.5623473525047302},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5021750926971436},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4759654402732849},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4272485375404358},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.41533392667770386},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40223273634910583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38949596881866455},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34220993518829346},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.13087493181228638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8489614725112915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6745094060897827},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6665862202644348},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6499588489532471},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6095523238182068},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.5837236642837524},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5632838606834412},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.5623473525047302},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5021750926971436},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4759654402732849},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4272485375404358},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.41533392667770386},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40223273634910583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38949596881866455},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34220993518829346},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.13087493181228638},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2962719","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2962719","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2489649360","display_name":null,"funder_award_id":"2012CB316304","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6884876748","display_name":null,"funder_award_id":"61225009, 61303173, 61432019, 61572498, 61532009, 61472379 and 61572296","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W189596042","https://openalex.org/W262578090","https://openalex.org/W1527575280","https://openalex.org/W1586939924","https://openalex.org/W1666447063","https://openalex.org/W1686810756","https://openalex.org/W1811254738","https://openalex.org/W1849277567","https://openalex.org/W1895577753","https://openalex.org/W1895989618","https://openalex.org/W1897761818","https://openalex.org/W1905882502","https://openalex.org/W1906515132","https://openalex.org/W1947481528","https://openalex.org/W1954433395","https://openalex.org/W1965555842","https://openalex.org/W1965963232","https://openalex.org/W1975517671","https://openalex.org/W1976529824","https://openalex.org/W1976948919","https://openalex.org/W1979246310","https://openalex.org/W1983364832","https://openalex.org/W1986397799","https://openalex.org/W2007510844","https://openalex.org/W2011261343","https://openalex.org/W2016053056","https://openalex.org/W2025768430","https://openalex.org/W2044686187","https://openalex.org/W2050103272","https://openalex.org/W2070057694","https://openalex.org/W2070753207","https://openalex.org/W2076434944","https://openalex.org/W2078238240","https://openalex.org/W2097117768","https://openalex.org/W2105101328","https://openalex.org/W2110798204","https://openalex.org/W2110933980","https://openalex.org/W2112796928","https://openalex.org/W2112912048","https://openalex.org/W2117539524","https://openalex.org/W2120615054","https://openalex.org/W2122084318","https://openalex.org/W2123024445","https://openalex.org/W2126574503","https://openalex.org/W2136922672","https://openalex.org/W2139501017","https://openalex.org/W2142900973","https://openalex.org/W2146502635","https://openalex.org/W2149557440","https://openalex.org/W2150979491","https://openalex.org/W2152984213","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2165935688","https://openalex.org/W2167905777","https://openalex.org/W2213713150","https://openalex.org/W2234733793","https://openalex.org/W2240344248","https://openalex.org/W2251353663","https://openalex.org/W2252254117","https://openalex.org/W2294978630","https://openalex.org/W2296385829","https://openalex.org/W2398936787","https://openalex.org/W2483327705","https://openalex.org/W2915649242","https://openalex.org/W2949447259","https://openalex.org/W2950133940","https://openalex.org/W2964241990","https://openalex.org/W2998508934","https://openalex.org/W4247950230","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2750434199","https://openalex.org/W2347374138","https://openalex.org/W2129428289","https://openalex.org/W2050635624","https://openalex.org/W2473933584","https://openalex.org/W2091753323","https://openalex.org/W2932687906","https://openalex.org/W2384506582","https://openalex.org/W2101447046","https://openalex.org/W2350165951"],"abstract_inverted_index":{"Content-based":[0],"video":[1,122],"understanding":[2],"is":[3,67,85],"extremely":[4],"difficult":[5],"due":[6],"to":[7,86,96,105],"the":[8,16,37,47,91,159,166],"semantic":[9,18,75,109],"gap":[10],"between":[11],"low-level":[12,43],"vision":[13],"signals":[14],"and":[15,22,49,163],"various":[17],"concepts":[19],"(object,":[20],"action,":[21],"scene)":[23],"in":[24],"videos.":[25],"Though":[26],"feature":[27],"extraction":[28,54],"from":[29,77,111],"videos":[30,78,89,112],"has":[31,55],"achieved":[32],"significant":[33],"progress,":[34],"most":[35],"of":[36,82,93],"previous":[38],"methods":[39],"rely":[40],"only":[41,114],"on":[42,73,145],"features,":[44],"such":[45],"as":[46],"appearance":[48],"motion":[50],"features.":[51],"Recently,":[52],"visual-feature":[53],"been":[56],"improved":[57],"significantly":[58,164],"with":[59,90,149],"machine-learning":[60],"algorithms,":[61],"especially":[62],"deep":[63],"learning.":[64],"However,":[65],"there":[66],"still":[68],"not":[69],"enough":[70],"work":[71],"focusing":[72],"extracting":[74],"features":[76,110],"directly.":[79],"The":[80],"goal":[81],"this":[83,126],"article":[84],"adopt":[87],"unlabeled":[88],"help":[92],"text":[94],"descriptions":[95],"learn":[97],"an":[98],"embedding":[99,132],"function,":[100],"which":[101],"can":[102],"be":[103],"used":[104],"extract":[106],"more":[107],"effective":[108],"when":[113],"a":[115,130],"few":[116],"labeled":[117],"samples":[118],"are":[119],"available":[120],"for":[121],"recognition.":[123],"To":[124],"achieve":[125],"goal,":[127],"we":[128],"propose":[129],"novel":[131],"convolutional":[133],"neural":[134],"network":[135],"(ECNN).":[136],"We":[137],"evaluate":[138],"our":[139],"algorithm":[140],"by":[141],"comparing":[142],"its":[143],"performance":[144],"three":[146],"challenging":[147],"benchmarks":[148],"several":[150],"popular":[151],"state-of-the-art":[152],"methods.":[153,168],"Extensive":[154],"experimental":[155],"results":[156],"show":[157],"that":[158],"proposed":[160],"ECNN":[161],"consistently":[162],"outperforms":[165],"existing":[167]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}