{"id":"https://openalex.org/W2951434650","doi":"https://doi.org/10.1109/iwbf.2019.8739178","title":"Analysis of hand-crafted and learned feature extraction methods for real-time facial expression recognition","display_name":"Analysis of hand-crafted and learned feature extraction methods for real-time facial expression recognition","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2951434650","doi":"https://doi.org/10.1109/iwbf.2019.8739178","mag":"2951434650"},"language":"en","primary_location":{"id":"doi:10.1109/iwbf.2019.8739178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbf.2019.8739178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 7th International Workshop on Biometrics and Forensics (IWBF)","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/A5034680605","display_name":"Jes\u00fas Olivares-Mercado","orcid":"https://orcid.org/0000-0002-0337-5364"},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Jesus Olivares-Mercado","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007704984","display_name":"Karina Toscano-Medina","orcid":null},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Karina Toscano-Medina","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113393295","display_name":"Gabriel S\u00e1nchez-P\u00e9rez","orcid":null},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Gabriel Sanchez-Perez","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012597502","display_name":"Jos\u00e9 Portillo-Portillo","orcid":"https://orcid.org/0000-0001-8863-7804"},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Jose Portillo-Portillo","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068877119","display_name":"H\u00e9ctor P\u00e9rez-Meana","orcid":"https://orcid.org/0000-0002-7786-2050"},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Hector Perez-Meana","raw_affiliation_strings":["Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico"],"affiliations":[{"raw_affiliation_string":"Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082384142","display_name":"Gibran Ben\u00edtez-Garc\u00eda","orcid":"https://orcid.org/0000-0003-4945-8314"},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gibran Benitez-Garcia","raw_affiliation_strings":["Toyota Technological Institute, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Nagoya, Japan","institution_ids":["https://openalex.org/I4840577"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5034680605"],"corresponding_institution_ids":["https://openalex.org/I59361560"],"apc_list":null,"apc_paid":null,"fwci":0.7086,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.74555939,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/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/T10667","display_name":"Emotion and Mood Recognition","score":0.9944000244140625,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.7757680416107178},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7507389187812805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6630351543426514},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6450755596160889},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.634244441986084},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5856476426124573},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.5253464579582214},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43432164192199707},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.40587228536605835},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3644596338272095},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08095303177833557}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7757680416107178},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7507389187812805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6630351543426514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6450755596160889},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.634244441986084},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5856476426124573},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.5253464579582214},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43432164192199707},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.40587228536605835},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3644596338272095},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08095303177833557},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwbf.2019.8739178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbf.2019.8739178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 7th International Workshop on Biometrics and Forensics (IWBF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1965947362","https://openalex.org/W2036803645","https://openalex.org/W2120281650","https://openalex.org/W2124773960","https://openalex.org/W2153635508","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W2164598857","https://openalex.org/W2165731615","https://openalex.org/W2297337743","https://openalex.org/W2298865080","https://openalex.org/W2472125875","https://openalex.org/W2569271273","https://openalex.org/W2612445135","https://openalex.org/W2738672149","https://openalex.org/W2799041689","https://openalex.org/W2800481460","https://openalex.org/W2804846320","https://openalex.org/W2884576348","https://openalex.org/W2891399311","https://openalex.org/W2908924275","https://openalex.org/W2963163009","https://openalex.org/W4231699953","https://openalex.org/W4245291335","https://openalex.org/W4297775537","https://openalex.org/W4403242122","https://openalex.org/W6737664043","https://openalex.org/W6749781174","https://openalex.org/W6750843368"],"related_works":["https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W1941834444","https://openalex.org/W2985118265","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2116055069","https://openalex.org/W4323520705","https://openalex.org/W2356663679","https://openalex.org/W2169777806"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2,115,125],"an":[3],"analysis":[4,19],"of":[5,24,55,69],"hand-crafted":[6],"and":[7,48,72,99,132],"learned":[8],"feature":[9,61],"extraction":[10],"methods":[11,22],"for":[12,75],"real-time":[13],"facial":[14,80],"expression":[15],"recognition":[16],"(FER).":[17],"Our":[18],"focuses":[20],"on":[21,26,86],"capable":[23],"running":[25],"mobile":[27],"devices,":[28],"including":[29],"traditional":[30],"algorithms":[31],"such":[32],"as":[33,38,40],"Gabor":[34],"transform,":[35],"HOG,":[36],"LBP,":[37],"well":[39],"two":[41,87],"compact":[42],"CNN":[43],"models,":[44],"named":[45],"Mobilenet":[46,123],"V1":[47],"V2.":[49],"Additionally,":[50],"we":[51,65],"test":[52],"the":[53,67,70,77,110,116,126],"performance":[54,118],"MOTIF,":[56],"a":[57],"highly":[58],"efficient":[59],"texture":[60],"extractor":[62],"algorithm.":[63],"Furthermore,":[64],"analyze":[66],"contribution":[68],"mouth":[71],"front-eyes":[73],"regions":[74],"recognizing":[76],"seven":[78],"basic":[79],"expressions.":[81],"Experimental":[82],"results":[83,128],"are":[84],"evaluated":[85],"publicly":[88],"available":[89],"datasets.":[90],"KDEF":[91],"database":[92,101],"which":[93,102],"was":[94],"captured":[95,107],"under":[96],"controlled":[97],"conditions":[98],"RAF":[100],"represents":[103],"more":[104],"naturalistic":[105],"expressions":[106],"in-the-wild.":[108],"Under":[109],"same":[111],"experimental":[112],"conditions,":[113],"MOTIF":[114],"fastest":[117],"by":[119],"sacrificing":[120],"accuracy,":[121],"while":[122],"V2":[124],"highest":[127],"with":[129],"considerable":[130],"speed":[131],"model":[133],"size.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}