{"id":"https://openalex.org/W2885352162","doi":"https://doi.org/10.1109/iwssip.2018.8439631","title":"Emotion Recognition from Occluded Facial Expressions Using Weber Local Descriptor","display_name":"Emotion Recognition from Occluded Facial Expressions Using Weber Local Descriptor","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2885352162","doi":"https://doi.org/10.1109/iwssip.2018.8439631","mag":"2885352162"},"language":"en","primary_location":{"id":"doi:10.1109/iwssip.2018.8439631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwssip.2018.8439631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP)","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/A5084115706","display_name":"Jadisha Yarif Ram\u00edrez Cornejo","orcid":"https://orcid.org/0000-0002-7283-1482"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Jadisha Yarif Ramirez Cornejo","raw_affiliation_strings":["Institute of Computing, University of Campinas, Campinas, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Computing, University of Campinas, Campinas, SP, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065725754","display_name":"H\u00e9lio Pedrini","orcid":"https://orcid.org/0000-0003-0125-630X"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Helio Pedrini","raw_affiliation_strings":["Institute of Computing, University of Campinas, Campinas, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Computing, University of Campinas, Campinas, SP, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084115706"],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":null,"apc_paid":null,"fwci":1.358,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.8594258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.984499990940094,"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/local-binary-patterns","display_name":"Local binary patterns","score":0.7780154943466187},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7397521138191223},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7311489582061768},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6638702750205994},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6526126861572266},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6483737230300903},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.6307462453842163},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6223464012145996},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5952586531639099},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5475963950157166},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5183557271957397},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4554339349269867},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.4448464512825012},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43714502453804016},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09525027871131897}],"concepts":[{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.7780154943466187},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7397521138191223},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7311489582061768},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6638702750205994},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6526126861572266},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6483737230300903},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.6307462453842163},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6223464012145996},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5952586531639099},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5475963950157166},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5183557271957397},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4554339349269867},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.4448464512825012},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43714502453804016},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09525027871131897},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwssip.2018.8439631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwssip.2018.8439631","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1154360701","https://openalex.org/W1540772689","https://openalex.org/W1584759658","https://openalex.org/W1736339626","https://openalex.org/W1913860614","https://openalex.org/W1967022116","https://openalex.org/W1970942140","https://openalex.org/W1976632974","https://openalex.org/W2001412060","https://openalex.org/W2032484416","https://openalex.org/W2038317184","https://openalex.org/W2039866355","https://openalex.org/W2083738729","https://openalex.org/W2103943262","https://openalex.org/W2130258210","https://openalex.org/W2145962650","https://openalex.org/W2170345688","https://openalex.org/W2218523284","https://openalex.org/W2251198138","https://openalex.org/W2296145878","https://openalex.org/W2296619321","https://openalex.org/W2308837722","https://openalex.org/W2327141690","https://openalex.org/W2401982790","https://openalex.org/W2580925984","https://openalex.org/W2583542555","https://openalex.org/W2625643342","https://openalex.org/W2963112684","https://openalex.org/W3099514962","https://openalex.org/W4231699953","https://openalex.org/W4250857377","https://openalex.org/W6640067882","https://openalex.org/W6697247078","https://openalex.org/W6713190629"],"related_works":["https://openalex.org/W2046724945","https://openalex.org/W4224879220","https://openalex.org/W2999130902","https://openalex.org/W3211626993","https://openalex.org/W2507467930","https://openalex.org/W4281681299","https://openalex.org/W4315797013","https://openalex.org/W2904398182","https://openalex.org/W2347245106","https://openalex.org/W2557833330"],"abstract_inverted_index":{"Recognition":[0],"of":[1,21,74,99],"emotions":[2],"based":[3,50],"on":[4,51,137],"facial":[5,26,52,66,87,154],"expressions":[6,53,67,155],"has":[7],"received":[8],"increasing":[9],"attention":[10],"from":[11,25,85],"the":[12,16,58,64,86,133,143,162],"scientific":[13],"community":[14],"over":[15],"last":[17],"years.":[18],"Several":[19],"fields":[20],"applications":[22],"can":[23],"benefit":[24],"emotion":[27,47],"recognition,":[28],"such":[29],"as":[30,90,92],"behavior":[31],"prediction,":[32],"interpersonal":[33],"relations,":[34],"human-computer":[35],"interactions,":[36],"recommendation":[37],"systems.":[38],"In":[39],"this":[40],"work,":[41],"we":[42],"develop":[43],"and":[44,97,114,123,152],"analyze":[45],"an":[46,71],"recognition":[48],"framework":[49],"robust":[54],"to":[55,131,157],"occlusions":[56],"through":[57],"Weber":[59],"Local":[60,93],"Descriptor":[61],"(WLD).":[62],"Initially,":[63],"occluded":[65,151],"are":[68,83,129],"reconstructed":[69],"following":[70],"extension":[72],"approach":[73],"Robust":[75],"Principal":[76,110],"Component":[77,111],"Analysis":[78,112,117],"(RPCA).":[79],"Then,":[80],"WLD":[81,144],"features":[82],"extracted":[84],"expression":[88],"representation,":[89],"well":[91],"Binary":[94],"Patterns":[95],"(LBP)":[96],"Histogram":[98],"Oriented":[100],"Gradients":[101],"(HOG).":[102],"The":[103],"feature":[104],"vector":[105],"space":[106],"is":[107],"reduced":[108],"using":[109],"(PCA)":[113],"Linear":[115],"Discriminant":[116],"(LDA).":[118],"Finally,":[119],"K-Nearest":[120],"Neighbor":[121],"(K-NN)":[122],"Support":[124],"Vector":[125],"Machine":[126],"(SVM)":[127],"classifiers":[128],"used":[130],"recognize":[132],"expressions.":[134],"Experimental":[135],"results":[136],"three":[138],"public":[139],"datasets":[140],"demonstrated":[141],"that":[142],"representation":[145],"achieved":[146],"competitive":[147],"accuracy":[148],"rates":[149],"for":[150],"non-occluded":[153],"compared":[156],"other":[158],"approaches":[159],"available":[160],"in":[161],"literature.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}