{"id":"https://openalex.org/W2126587529","doi":"https://doi.org/10.1109/wacv.2009.5403085","title":"Age categorization via ECOC with fused gabor and LBP features","display_name":"Age categorization via ECOC with fused gabor and LBP features","publication_year":2009,"publication_date":"2009-12-01","ids":{"openalex":"https://openalex.org/W2126587529","doi":"https://doi.org/10.1109/wacv.2009.5403085","mag":"2126587529"},"language":"en","primary_location":{"id":"doi:10.1109/wacv.2009.5403085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2009.5403085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Workshop on Applications of Computer Vision (WACV)","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/A5115594803","display_name":"Jiangang Wang","orcid":null},"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":true,"raw_author_name":"Jian-Gang Wang","raw_affiliation_strings":["Institute for Infocomm Research, Singapore","Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057104857","display_name":"Wei\u2010Yun Yau","orcid":"https://orcid.org/0000-0001-5709-9169"},"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":"Wei-Yun Yau","raw_affiliation_strings":["Institute for Infocomm Research, Singapore","Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112222922","display_name":"Hee Lin Wang","orcid":null},"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":"Hee Lin Wang","raw_affiliation_strings":["Institute for Infocomm Research, Singapore","Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore"],"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Institute for Infocomm Research, 1 Fusionpolis Way, #21-01, Connexis Singapore 138632, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5115594803"],"corresponding_institution_ids":["https://openalex.org/I3005327000"],"apc_list":null,"apc_paid":null,"fwci":5.1771,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.95911899,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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/T10057","display_name":"Face and Expression Recognition","score":0.9951000213623047,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9812999963760376,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7383646368980408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7317479848861694},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6837247610092163},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.622154951095581},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5958740711212158},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.5713151693344116},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5548782348632812},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5285666584968567},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48975467681884766},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4524000883102417},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.45155465602874756},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.19575437903404236},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.06466811895370483}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7383646368980408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7317479848861694},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6837247610092163},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.622154951095581},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5958740711212158},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.5713151693344116},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5548782348632812},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5285666584968567},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48975467681884766},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4524000883102417},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.45155465602874756},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.19575437903404236},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.06466811895370483},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv.2009.5403085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2009.5403085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Workshop on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.46000000834465027,"display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1213294141","https://openalex.org/W1578772208","https://openalex.org/W1676820704","https://openalex.org/W1966045914","https://openalex.org/W1981863521","https://openalex.org/W1988790447","https://openalex.org/W2032454342","https://openalex.org/W2039140324","https://openalex.org/W2112496463","https://openalex.org/W2115857118","https://openalex.org/W2118664399","https://openalex.org/W2118755929","https://openalex.org/W2121939926","https://openalex.org/W2132103241","https://openalex.org/W2134113392","https://openalex.org/W2135994945","https://openalex.org/W2137802466","https://openalex.org/W2144119003","https://openalex.org/W2147278565","https://openalex.org/W2163352848","https://openalex.org/W2163626514","https://openalex.org/W2170854557","https://openalex.org/W2182517799","https://openalex.org/W2885641121","https://openalex.org/W3097096317","https://openalex.org/W4285719527","https://openalex.org/W6634795092","https://openalex.org/W6680136119","https://openalex.org/W6680167234"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561"],"abstract_inverted_index":{"Face":[0],"image":[1],"based":[2,96],"age":[3,112],"categorization":[4,62,113],"is":[5,19,25,32,63,79,167],"an":[6],"approach":[7],"to":[8,27,109,128,142],"classify":[9],"face":[10,131],"images":[11],"into":[12],"one":[13,188],"of":[14,68,82,85],"several":[15],"pre-defined":[16],"age-groups.":[17],"It":[18],"challenging":[20],"because":[21],"the":[22,37,69,76,80,83,111,125,130,178,187],"aging":[23,118],"variation":[24],"specific":[26],"a":[28,64,93],"given":[29],"individual":[30],"and":[31,58,116,122,137,146,181],"determined":[33],"by":[34,42],"not":[35],"only":[36],"person's":[38],"gene,":[39],"but":[40],"also":[41],"many":[43],"external":[44],"factors,":[45],"such":[46],"as":[47],"exposure,":[48],"weather":[49],"conditions":[50],"(e.g.":[51],"ambient":[52],"humidity),":[53],"health,":[54],"gender,":[55],"living":[56,59],"style":[57],"location.":[60],"Age":[61],"multiclass":[65,77],"problem.":[66,114],"One":[67],"AdaBoost":[70,160,166],"or":[71,98,161,193],"SVM":[72,100],"extensions":[73],"for":[74],"solving":[75],"problem":[78],"combination":[81],"method":[84],"error-correcting":[86],"output":[87],"codes":[88],"(ECOC)":[89],"with":[90,159],"boosting":[91],"using":[92,177,190],"decision":[94],"tree":[95],"classifier":[97],"binary":[99],"classifier.":[101],"In":[102],"this":[103,107],"paper,":[104],"we":[105],"apply":[106],"extension":[108],"solve":[110],"Gabor":[115,182,194],"LBP":[117,180,192],"features":[119,183],"are":[120,140,184],"extracted":[121],"combined":[123,158],"at":[124],"feature":[126],"level":[127],"represent":[129],"images.":[132],"Experimental":[133],"results":[134,154,175],"on":[135],"FG-NET":[136],"Morph":[138],"database":[139],"reported":[141],"demonstrate":[143],"its":[144],"effectiveness":[145],"robustness.":[147],"The":[148,174],"ECOC":[149,164,171],"can":[150],"achieve":[151],"nearly":[152],"similar":[153],"when":[155,189],"it":[156],"was":[157],"SVM.":[162,173],"However,":[163],"plus":[165,172],"much":[168],"faster":[169],"than":[170,186],"obtained":[176],"fused":[179],"better":[185],"either":[191],"alone.":[195]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}