{"id":"https://openalex.org/W2756106545","doi":"https://doi.org/10.1109/icip.2017.8296594","title":"4D effect classification by encoding CNN features","display_name":"4D effect classification by encoding CNN features","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2756106545","doi":"https://doi.org/10.1109/icip.2017.8296594","mag":"2756106545"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5045592891","display_name":"Thomhert Suprapto Siadari","orcid":"https://orcid.org/0000-0001-7811-0953"},"institutions":[{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Thomhert S. Siadari","raw_affiliation_strings":["Korea University of Science and Technology, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea University of Science and Technology, South Korea","institution_ids":["https://openalex.org/I88761825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112677842","display_name":"Mikyong Han","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mikyong Han","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, South Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049559685","display_name":"Hyunjin Yoon","orcid":"https://orcid.org/0000-0002-2252-9402"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]},{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunjin Yoon","raw_affiliation_strings":["Electronics and Telecommunications Research Institute, South Korea","Korea University of Science and Technology, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute, South Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Korea University of Science and Technology, South Korea","institution_ids":["https://openalex.org/I88761825"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0796,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.36599333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"115","issue":null,"first_page":"1812","last_page":"1816"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9965000152587891,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9965000152587891,"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":0.9950000047683716,"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/T10648","display_name":"Virtual Reality Applications and Impacts","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.8421425223350525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6856683492660522},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6175515651702881},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5541804432868958},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5336585640907288},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5054264068603516},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49731114506721497},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.41883039474487305},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3650023341178894},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3346327543258667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8421425223350525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6856683492660522},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6175515651702881},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5541804432868958},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5336585640907288},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5054264068603516},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49731114506721497},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.41883039474487305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3650023341178894},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3346327543258667}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296594","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296594","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1532470821","https://openalex.org/W1546411676","https://openalex.org/W1686810756","https://openalex.org/W1784731433","https://openalex.org/W1849277567","https://openalex.org/W1875160599","https://openalex.org/W1950136256","https://openalex.org/W2016053056","https://openalex.org/W2022508996","https://openalex.org/W2049296440","https://openalex.org/W2062118960","https://openalex.org/W2101234009","https://openalex.org/W2102605133","https://openalex.org/W2117539524","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W2167510172","https://openalex.org/W2253891449","https://openalex.org/W2963542991","https://openalex.org/W2963992782","https://openalex.org/W4298372712","https://openalex.org/W4318895401","https://openalex.org/W6639204139","https://openalex.org/W6675354045","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3211292372","https://openalex.org/W2810679507"],"abstract_inverted_index":{"4D":[0,27,64,88,147],"effects":[1,4,28,53,65],"are":[2,66,123,133],"physical":[3,52],"simulated":[5],"in":[6,18,68,171],"sync":[7],"with":[8,157],"videos,":[9],"movies,":[10],"and":[11,46,72,84,107,141,151],"games":[12],"to":[13,82,102,135,169],"augment":[14],"the":[15,32,49,79,166],"events":[16],"occurring":[17],"a":[19,22,55,109],"story":[20],"or":[21],"virtual":[23],"world.":[24],"Types":[25],"of":[26,51,87,97,139,144,173],"commonly":[29],"used":[30],"for":[31,146],"immersive":[33,70],"media":[34],"may":[35],"include":[36],"seat":[37],"motion,":[38],"vibration,":[39],"flash,":[40],"wind,":[41],"water,":[42],"scent,":[43],"thunderstorm,":[44],"snow,":[45],"fog.":[47],"Currently,":[48],"recognition":[50],"from":[54],"video":[56,118,160],"is":[57],"mainly":[58],"conducted":[59,124],"by":[60,125],"human":[61],"experts.":[62],"Although":[63],"promising":[67],"giving":[69],"experience":[71],"entertainment,":[73],"this":[74,91],"manual":[75],"production":[76],"has":[77],"been":[78],"main":[80],"obstacle":[81],"faster":[83],"wider":[85],"application":[86],"effects.":[89],"In":[90],"paper,":[92],"we":[93],"utilize":[94],"pretrained":[95],"models":[96],"Convolutional":[98],"Neural":[99],"Networks":[100],"(CNNs)":[101],"extract":[103],"local":[104],"visual":[105],"features":[106,116,145],"propose":[108],"new":[110],"representation":[111],"method":[112,156],"that":[113],"combines":[114],"extracted":[115],"into":[117],"level":[119,161],"features.":[120],"Classification":[121],"tasks":[122],"employing":[126],"Support":[127],"Vector":[128],"Machine":[129],"(SVM).":[130],"Comprehensive":[131],"experiments":[132],"performed":[134],"investigate":[136],"different":[137,142],"architecture":[138],"CNNs":[140],"type":[143],"effect":[148],"classification":[149],"task":[150],"compare":[152],"baseline":[153,167],"average":[154,175],"pooling":[155],"our":[158],"proposed":[159],"representation.":[162],"Our":[163],"framework":[164],"outperforms":[165],"up":[168],"2-3%":[170],"terms":[172],"mean":[174],"precision":[176],"(mAP).":[177]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}