{"id":"https://openalex.org/W2515036155","doi":"https://doi.org/10.1109/icip.2016.7532434","title":"Multi-scale blocks based image emotion classification using multiple instance learning","display_name":"Multi-scale blocks based image emotion classification using multiple instance learning","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2515036155","doi":"https://doi.org/10.1109/icip.2016.7532434","mag":"2515036155"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","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/A5083624141","display_name":"Tianrong Rao","orcid":"https://orcid.org/0000-0001-9297-2277"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Tianrong Rao","raw_affiliation_strings":["Faculty of Engineering and IT, University of Technology, Sydney"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and IT, University of Technology, Sydney","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100413849","display_name":"Min Xu","orcid":"https://orcid.org/0000-0001-9581-8849"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Min Xu","raw_affiliation_strings":["Faculty of Engineering and IT, University of Technology, Sydney"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and IT, University of Technology, Sydney","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100773180","display_name":"Huiying Liu","orcid":"https://orcid.org/0000-0002-6405-1187"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Huiying Liu","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058420913","display_name":"Jinqiao Wang","orcid":"https://orcid.org/0000-0002-9118-2780"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinqiao Wang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030755672","display_name":"Lee Burnett","orcid":"https://orcid.org/0000-0003-3795-7722"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ian Burnett","raw_affiliation_strings":["Faculty of Engineering and IT, University of Technology, Sydney"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and IT, University of Technology, Sydney","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5083624141"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":3.21,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.94853874,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"634","last_page":"638"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9961000084877014,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7344479560852051},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5977140665054321},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5781276822090149},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5518471002578735},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5197619795799255},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5185406804084778},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48539459705352783},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37096571922302246},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3504795730113983}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7344479560852051},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5977140665054321},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5781276822090149},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5518471002578735},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5197619795799255},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5185406804084778},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48539459705352783},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37096571922302246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3504795730113983},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2016.7532434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/56154","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/56154","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1540386283","https://openalex.org/W1589362500","https://openalex.org/W2003856922","https://openalex.org/W2011664673","https://openalex.org/W2074356411","https://openalex.org/W2085940040","https://openalex.org/W2098935012","https://openalex.org/W2107034620","https://openalex.org/W2118246710","https://openalex.org/W2118526556","https://openalex.org/W2119902719","https://openalex.org/W2144459292","https://openalex.org/W2295328086","https://openalex.org/W2974550657","https://openalex.org/W6632200337","https://openalex.org/W7075742223"],"related_works":["https://openalex.org/W4391026046","https://openalex.org/W4256291048","https://openalex.org/W4255358048","https://openalex.org/W2782696245","https://openalex.org/W1147368348","https://openalex.org/W2361379498","https://openalex.org/W3030538550","https://openalex.org/W2160121913","https://openalex.org/W2736149021","https://openalex.org/W4392809305"],"abstract_inverted_index":{"Emotional":[0],"factors":[1],"usually":[2],"affect":[3],"users'":[4],"preferences":[5],"for":[6,158],"and":[7,56,59,111,117],"evaluations":[8],"of":[9,69,98,149,169,192],"images.":[10],"Although":[11],"affective":[12],"image":[13,32,43,72,100,106,193],"analysis":[14,135],"attracts":[15],"increasing":[16],"attention,":[17],"there":[18,49],"are":[19],"still":[20],"three":[21,77,176],"major":[22],"challenges":[23],"remaining:":[24],"1)":[25],"it":[26,61],"is":[27,50,62,137,161],"difficult":[28,63],"to":[29,64,127,139,163],"classify":[30,164],"an":[31,42,81,99],"into":[33],"a":[34,51,66,146],"single":[35],"emotion":[36,82,167,194],"type":[37,168],"since":[38],"different":[39,46,105],"regions":[40],"within":[41],"can":[44],"represent":[45,118],"emotions;":[47],"2)":[48],"gap":[52],"between":[53],"low-level":[54],"features":[55],"high-level":[57],"emotions":[58],"3)":[60],"collect":[65],"training":[67],"set":[68],"reliable":[70],"emotional":[71],"content.":[73],"To":[74],"address":[75],"these":[76],"issues,":[78],"we":[79],"propose":[80],"classification":[83,195],"method":[84,184],"based":[85],"on":[86,175,197],"multi-scale":[87],"blocks":[88,97],"using":[89,104,121],"Multiple":[90],"Instance":[91],"Learning":[92],"(MIL).":[93],"We":[94],"firstly":[95],"extract":[96],"at":[101],"multiple":[102],"scales":[103],"segmentation":[107,110],"methods":[108],"pyramid":[109],"simple":[112],"linear":[113],"iterative":[114],"clustering":[115],"(SLIC)":[116],"each":[119,150],"block":[120],"the":[122,129,141,156,165,170,189],"bag-of-visual-words":[123],"(BoVW)":[124],"method.":[125],"Then,":[126],"bridge":[128],"\u201caffective":[130],"gap\u201d,":[131],"probabilistic":[132],"latent":[133,142],"semantic":[134],"(pLSA)":[136],"employed":[138,162],"estimate":[140],"topic":[143],"distribution":[144],"as":[145],"mid-level":[147],"representation":[148],"block.":[151],"Finally,":[152],"MIL,":[153],"which":[154],"reduces":[155],"need":[157],"exact":[159],"labelling,":[160],"dominant":[166],"image.":[171],"Experiments":[172],"carried":[173],"out":[174],"widely":[177],"used":[178],"datasets":[179],"demonstrate":[180],"that":[181],"our":[182],"proposed":[183],"with":[185],"S-LIC":[186],"effectively":[187],"improves":[188],"state-of-the-art":[190],"results":[191],"5.1%":[196],"average.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}