{"id":"https://openalex.org/W2891596343","doi":"https://doi.org/10.1109/icip.2018.8451358","title":"Double Complete D-LBP with Extreme Learning Machine Auto-Encoder and Cascade Forest for Facial Expression Analysis","display_name":"Double Complete D-LBP with Extreme Learning Machine Auto-Encoder and Cascade Forest for Facial Expression Analysis","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2891596343","doi":"https://doi.org/10.1109/icip.2018.8451358","mag":"2891596343"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th 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/A5011477215","display_name":"Fang Shen","orcid":"https://orcid.org/0000-0002-1988-9714"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Shen","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375038","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0002-6834-5350"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Liu","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032693575","display_name":"Peng Wu","orcid":"https://orcid.org/0000-0003-2938-6798"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wu","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.3803,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71496104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"32","issue":null,"first_page":"1947","last_page":"1951"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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/T10057","display_name":"Face and Expression Recognition","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/T12676","display_name":"Machine Learning and ELM","score":0.9980000257492065,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9951000213623047,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.9135509133338928},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7182157039642334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7126286029815674},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6672323942184448},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6206918954849243},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.582876443862915},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5557533502578735},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5282644033432007},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47720322012901306},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.4753448963165283},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.47402623295783997},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.440543532371521},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4223955273628235},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.4139527380466461},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3546530604362488},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.1518259048461914},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11597311496734619},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10586941242218018},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08894315361976624}],"concepts":[{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.9135509133338928},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7182157039642334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7126286029815674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6672323942184448},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6206918954849243},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.582876443862915},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5557533502578735},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5282644033432007},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47720322012901306},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.4753448963165283},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.47402623295783997},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.440543532371521},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4223955273628235},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.4139527380466461},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3546530604362488},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.1518259048461914},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11597311496734619},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10586941242218018},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08894315361976624},{"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/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6800000071525574,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1573760330","https://openalex.org/W1866173756","https://openalex.org/W1981918162","https://openalex.org/W1989188126","https://openalex.org/W2068908391","https://openalex.org/W2083021723","https://openalex.org/W2096044434","https://openalex.org/W2103943262","https://openalex.org/W2104563967","https://openalex.org/W2106115875","https://openalex.org/W2125127226","https://openalex.org/W2145310492","https://openalex.org/W2147141800","https://openalex.org/W2161634108","https://openalex.org/W2163352848","https://openalex.org/W2163808566","https://openalex.org/W2198512331","https://openalex.org/W2244142460","https://openalex.org/W2343258859","https://openalex.org/W2358858333","https://openalex.org/W2408701322","https://openalex.org/W2479148236","https://openalex.org/W2592340788","https://openalex.org/W2597016113","https://openalex.org/W2604209953","https://openalex.org/W2626494122","https://openalex.org/W2738672149","https://openalex.org/W6639348618","https://openalex.org/W6687716273","https://openalex.org/W6704724379"],"related_works":["https://openalex.org/W2583894904","https://openalex.org/W2144004426","https://openalex.org/W1990254706","https://openalex.org/W2404514746","https://openalex.org/W1843372508","https://openalex.org/W3208297503","https://openalex.org/W3119773509","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611"],"abstract_inverted_index":{"Although":[0],"the":[1,14,64,72,85,118,125,131,139,146],"obtained":[2],"accuracy":[3],"on":[4,145,164],"some":[5],"lab-controlled":[6,153],"facial":[7,17,37,51,75,148],"expression":[8,38,52,149],"datasets":[9],"has":[10],"been":[11],"very":[12],"high,":[13],"recognition":[15],"of":[16,45,74,87],"expressions":[18],"in":[19,36],"wild":[20,155],"environments":[21,156],"is":[22,31,93,106,136],"still":[23],"a":[24,32,59],"challenging":[25],"problem.":[26],"Local":[27],"Binary":[28],"Patterns":[29],"(LBP)":[30],"widely":[33],"used":[34,94],"operator":[35],"recognition.":[39,53],"However,":[40],"there":[41],"are":[42,79],"few":[43],"variations":[44],"LBP":[46,92,105],"operators":[47],"specifically":[48],"designed":[49],"for":[50],"In":[54],"this":[55],"paper,":[56],"we":[57],"propose":[58],"novel":[60],"representation":[61],"approach":[62,128],"called":[63],"Double":[65],"Complete":[66],"d-LBP":[67,78],"(Double":[68],"Cd-LBP)":[69],"according":[70],"to":[71,81,95,108,129],"characteristics":[73],"expressions.":[76],"Two":[77],"employed":[80,137],"represent":[82],"details":[83],"and":[84,90,98,112,154],"contour":[86],"faces":[88],"separately,":[89],"complete":[91],"take":[96],"sign":[97],"magnitude":[99],"components":[100],"into":[101],"account.":[102],"Moreover,":[103],"multi-scale":[104],"exploited":[107],"obtain":[109],"local":[110],"texture":[111],"global":[113],"information.":[114],"We":[115],"then":[116],"use":[117],"extreme":[119],"learning":[120],"machine":[121],"auto-encoder":[122],"(ELM-AE)":[123],"as":[124,138],"feature":[126],"selection":[127],"learn":[130],"discriminative":[132],"feature.":[133],"Cascade":[134],"forest":[135],"final":[140],"decision":[141],"classifier.":[142],"Experiments":[143],"conducted":[144],"six":[147],"databases,":[150,157],"including":[151],"both":[152],"show":[158],"that":[159],"our":[160],"method":[161],"outperforms":[162],"or":[163],"par":[165],"with":[166],"state-of-the-arts.":[167]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
