{"id":"https://openalex.org/W2552190925","doi":"https://doi.org/10.1109/ijcnn.2016.7727484","title":"Smile detection using Pair-wise Distance Vector and Extreme Learning Machine","display_name":"Smile detection using Pair-wise Distance Vector and Extreme Learning Machine","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2552190925","doi":"https://doi.org/10.1109/ijcnn.2016.7727484","mag":"2552190925"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727484","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5057937760","display_name":"Dongshun Cui","orcid":"https://orcid.org/0000-0002-9703-0120"},"institutions":[{"id":"https://openalex.org/I4210094970","display_name":"Energy Research Institute","ror":"https://ror.org/00ndnb620","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094970","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongshun Cui","raw_affiliation_strings":["Energy Research Institute @NTU (ERI@N), Interdisciplinary Graduate School"],"affiliations":[{"raw_affiliation_string":"Energy Research Institute @NTU (ERI@N), Interdisciplinary Graduate School","institution_ids":["https://openalex.org/I4210094970"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061746912","display_name":"Guang-Bin Huang","orcid":"https://orcid.org/0000-0002-2480-4965"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Guang-Bin Huang","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101486718","display_name":"Tianchi Liu","orcid":"https://orcid.org/0000-0001-6733-3924"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Tianchi Liu","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057937760"],"corresponding_institution_ids":["https://openalex.org/I4210094970"],"apc_list":null,"apc_paid":null,"fwci":2.0041,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.91306829,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"14","issue":null,"first_page":"2298","last_page":"2305"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9979000091552734,"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":0.9979000091552734,"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":0.9940999746322632,"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/T11448","display_name":"Face recognition and analysis","score":0.974399983882904,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7564791440963745},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7368113994598389},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6300298571586609},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6288809180259705},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.616804838180542},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6079066395759583},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.6066309213638306},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5569886565208435},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5514081120491028},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5075994729995728},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44781258702278137},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4469864070415497},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4333629012107849},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.17984429001808167},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17366984486579895}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7564791440963745},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7368113994598389},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6300298571586609},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6288809180259705},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.616804838180542},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6079066395759583},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.6066309213638306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5569886565208435},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5514081120491028},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5075994729995728},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44781258702278137},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4469864070415497},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4333629012107849},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.17984429001808167},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17366984486579895},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727484","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5299999713897705,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1533211791","https://openalex.org/W1596717185","https://openalex.org/W1607979445","https://openalex.org/W1680392829","https://openalex.org/W1796263212","https://openalex.org/W1865042792","https://openalex.org/W1913860614","https://openalex.org/W1968600824","https://openalex.org/W1977821862","https://openalex.org/W2004014581","https://openalex.org/W2008933718","https://openalex.org/W2031187406","https://openalex.org/W2040482041","https://openalex.org/W2071128523","https://openalex.org/W2078040488","https://openalex.org/W2081821057","https://openalex.org/W2082308025","https://openalex.org/W2086795172","https://openalex.org/W2094056275","https://openalex.org/W2098290011","https://openalex.org/W2103384342","https://openalex.org/W2111072639","https://openalex.org/W2111461298","https://openalex.org/W2112545404","https://openalex.org/W2114826417","https://openalex.org/W2129601604","https://openalex.org/W2130177765","https://openalex.org/W2145413816","https://openalex.org/W2149382413","https://openalex.org/W2151103935","https://openalex.org/W2154003683","https://openalex.org/W2157653492","https://openalex.org/W2158695872","https://openalex.org/W2160367227","https://openalex.org/W2161969291","https://openalex.org/W2166694921","https://openalex.org/W2185532022","https://openalex.org/W6637386731","https://openalex.org/W6640067882","https://openalex.org/W6683411478"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W1584764049","https://openalex.org/W2743832667","https://openalex.org/W4386889652"],"abstract_inverted_index":{"A":[0],"smile":[1,29,52,82,100,141],"is":[2,30,121,137],"a":[3,28,39,51,98,104,113,129],"common":[4],"human":[5],"facial":[6],"expression":[7],"used":[8],"as":[9],"the":[10,34,54,58,89,92,158],"indicator":[11],"for":[12,22,49],"positive":[13],"emotion.":[14],"The":[15,146],"detection":[16],"of":[17,36,60,109,163,167],"smiling":[18],"has":[19],"many":[20],"applications,":[21],"example,":[23],"controlling":[24],"camera":[25],"shutter":[26],"when":[27],"detected":[31],"and":[32,84,106,165],"measuring":[33],"degree":[35],"satisfaction":[37],"during":[38],"video":[40],"conference.":[41],"Many":[42],"feature":[43,63,114],"extraction":[44],"methods":[45,160],"have":[46],"been":[47],"proposed":[48,155],"detecting":[50],"in":[53,161],"unconstrained":[55],"scenarios.":[56],"However,":[57],"dimensions":[59],"most":[61],"existing":[62],"descriptors":[64],"are":[65],"too":[66],"huge,":[67],"which":[68,120],"limits":[69],"their":[70],"real":[71],"applications.":[72],"Moreover,":[73],"features":[74,110],"should":[75],"be":[76],"more":[77],"effective":[78],"to":[79,139],"distinguish":[80],"between":[81],"face":[83],"non-smile":[85],"face.":[86],"Motivated":[87],"by":[88],"observation":[90],"that":[91,111,153],"mouth":[93],"shape":[94],"can":[95],"effectively":[96],"reflect":[97],"person's":[99],"state,":[101],"we":[102],"extracted":[103],"novel":[105],"snappy":[107],"set":[108],"form":[112],"vector":[115],"named":[116],"Pair-wise":[117],"Distance":[118],"Vector,":[119],"calculated":[122],"only":[123],"based":[124,142],"on":[125,143,149],"few":[126],"points":[127],"around":[128],"mouth.":[130],"After":[131],"that,":[132],"Extreme":[133],"Learning":[134],"Machine":[135],"(ELM)":[136],"adopted":[138],"classify":[140],"these":[144],"features.":[145,168],"experimental":[147],"results":[148],"GENKI-4K":[150],"database":[151],"show":[152],"our":[154],"method":[156],"outperforms":[157],"state-of-the-art":[159],"terms":[162],"accuracy":[164],"dimension":[166]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}