{"id":"https://openalex.org/W2786562281","doi":"https://doi.org/10.1109/btas.2017.8272747","title":"In defense of low-level structural features and SVMs for facial attribute classification: Application to detection of eye state, Mouth State, and eyeglasses in the wild","display_name":"In defense of low-level structural features and SVMs for facial attribute classification: Application to detection of eye state, Mouth State, and eyeglasses in the wild","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2786562281","doi":"https://doi.org/10.1109/btas.2017.8272747","mag":"2786562281"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2017.8272747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","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/A5036171667","display_name":"Abdulaziz Alorf","orcid":"https://orcid.org/0000-0002-2747-528X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abdulaziz Alorf","raw_affiliation_strings":["Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065400092","display_name":"A. Lynn Abbott","orcid":"https://orcid.org/0000-0003-3850-6771"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Lynn Abbott","raw_affiliation_strings":["Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036171667"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.2731,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66017764,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"599","last_page":"607"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991000294685364,"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":0.9991000294685364,"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/T11448","display_name":"Face recognition and analysis","score":0.9986000061035156,"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/T11094","display_name":"Face Recognition and Perception","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6911503076553345},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6389831304550171},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5984205603599548},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5895407199859619},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.44902217388153076},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.42300665378570557},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3854672908782959},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3244226574897766},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08708590269088745}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6911503076553345},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6389831304550171},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5984205603599548},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5895407199859619},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.44902217388153076},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.42300665378570557},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3854672908782959},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3244226574897766},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08708590269088745}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/btas.2017.8272747","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272747","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1526622935","https://openalex.org/W1599238028","https://openalex.org/W1782590233","https://openalex.org/W1834627138","https://openalex.org/W1903127635","https://openalex.org/W1963882359","https://openalex.org/W1968952909","https://openalex.org/W1976376589","https://openalex.org/W1979931042","https://openalex.org/W1985636418","https://openalex.org/W1998294030","https://openalex.org/W2035379092","https://openalex.org/W2038044681","https://openalex.org/W2109235804","https://openalex.org/W2110033722","https://openalex.org/W2119605622","https://openalex.org/W2132565621","https://openalex.org/W2138406903","https://openalex.org/W2141303268","https://openalex.org/W2144172034","https://openalex.org/W2145072179","https://openalex.org/W2147414309","https://openalex.org/W2150025598","https://openalex.org/W2151103935","https://openalex.org/W2151343288","https://openalex.org/W2152826865","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2163808566","https://openalex.org/W2167272056","https://openalex.org/W2194775991","https://openalex.org/W2536626143","https://openalex.org/W2963025229","https://openalex.org/W2963340555","https://openalex.org/W3105024549","https://openalex.org/W4297791040","https://openalex.org/W6635793669","https://openalex.org/W6640442106","https://openalex.org/W6681239517","https://openalex.org/W6681554747","https://openalex.org/W6684191040","https://openalex.org/W6684278770","https://openalex.org/W6785761061"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2347824352","https://openalex.org/W2112875849"],"abstract_inverted_index":{"The":[0,178],"current":[1],"trend":[2],"in":[3,39,115],"image":[4],"analysis":[5],"is":[6],"to":[7,35,88,108,152],"employ":[8],"automatically":[9],"detected":[10],"feature":[11],"types,":[12],"such":[13,27],"as":[14,28,106],"those":[15],"obtained":[16,56],"using":[17,97,189],"deep-learning":[18,109],"techniques.":[19],"For":[20],"some":[21],"applications,":[22],"however,":[23],"manually":[24],"crafted":[25],"features":[26],"Histogram":[29],"of":[30,50,61,127,136],"Oriented":[31],"Gradients":[32],"(HOG)":[33],"continue":[34],"yield":[36],"better":[37,95],"performance":[38,96,150],"demanding":[40],"situations.":[41],"This":[42],"paper":[43],"considers":[44],"both":[45],"approaches":[46,110],"for":[47,54,174],"the":[48,58,116,130,139,166,175],"problem":[49],"facial":[51],"attribute":[52,89],"classification,":[53],"images":[55],"\u201cin":[57],"wild.\u201d":[59],"Attributes":[60],"particular":[62],"interest":[63],"are":[64],"eye":[65,121],"state":[66,69],"(open/closed),":[67,70],"mouth":[68,146],"and":[71,133,171],"eyeglasses":[72,159],"(present/absent).":[73],"We":[74],"present":[75],"a":[76,100,190],"full":[77],"face-processing":[78],"pipeline":[79],"that":[80,111],"employs":[81],"conventional":[82,101],"machine":[83,103],"learning":[84],"techniques,":[85],"from":[86],"detection":[87],"classification.":[90],"Experimental":[91],"results":[92],"have":[93,112],"indicated":[94],"RootSIFT":[98],"with":[99],"support-vector":[102],"(SVM)":[104],"approach,":[105],"compared":[107],"been":[113],"reported":[114,180],"literature.":[117],"Our":[118],"proposed":[119,144,157],"open/closed":[120,145],"classifier":[122,147,160],"has":[123,148],"yielded":[124],"an":[125,134],"accuracy":[126,135],"99.3%":[128],"on":[129,138,169,186],"CEW":[131],"dataset,":[132],"98.7%":[137],"ZJU":[140],"dataset.":[141,177],"Similarly,":[142],"our":[143,156],"achieved":[149],"similar":[151],"deep":[153],"learning.":[154],"Also,":[155],"presence/absence":[158],"delivered":[161],"very":[162],"good":[163],"performance,":[164],"being":[165],"best":[167,173],"method":[168],"LFWA,":[170],"second":[172],"CelebA":[176],"system":[179],"here":[181],"runs":[182],"at":[183],"30":[184],"fps":[185],"HD-sized":[187],"video":[188],"CPU-only":[191],"implementation.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
