{"id":"https://openalex.org/W1998815328","doi":"https://doi.org/10.1109/btas.2013.6712697","title":"SNoW: Understanding the causes of strong, neutral, and weak face impostor pairs","display_name":"SNoW: Understanding the causes of strong, neutral, and weak face impostor pairs","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W1998815328","doi":"https://doi.org/10.1109/btas.2013.6712697","mag":"1998815328"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2013.6712697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2013.6712697","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)","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/A5073107879","display_name":"Amanda Sgroi","orcid":null},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Amanda Sgroi","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN","University of Notre Dame, Notre Dame, IN USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019673624","display_name":"Kevin W. Bowyer","orcid":"https://orcid.org/0000-0002-7562-4390"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin W. Bowyer","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN","University of Notre Dame, Notre Dame, IN USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039987576","display_name":"Patrick J. Flynn","orcid":"https://orcid.org/0000-0002-5446-114X"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Patrick Flynn","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN","University of Notre Dame, Notre Dame, IN USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN","institution_ids":["https://openalex.org/I107639228"]},{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047918353","display_name":"P. Jonathon Phillips","orcid":"https://orcid.org/0000-0001-6284-5197"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P. Jonathon Phillips","raw_affiliation_strings":["NIST Gaithersburg, MD","NIST, Gaithersburg, MD, USA"],"affiliations":[{"raw_affiliation_string":"NIST Gaithersburg, MD","institution_ids":[]},{"raw_affiliation_string":"NIST, Gaithersburg, MD, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073107879"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":0.8293,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75757104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.988099992275238,"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":0.988099992275238,"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":0.967199981212616,"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/T10057","display_name":"Face and Expression Recognition","score":0.951200008392334,"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/partition","display_name":"Partition (number theory)","score":0.6237404346466064},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.6055824160575867},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5653116106987},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5614822506904602},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.545793354511261},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.539929986000061},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4931299388408661},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4867527484893799},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4323327839374542},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29623639583587646},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.16260963678359985}],"concepts":[{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6237404346466064},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6055824160575867},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5653116106987},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5614822506904602},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.545793354511261},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.539929986000061},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4931299388408661},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4867527484893799},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4323327839374542},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29623639583587646},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.16260963678359985},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/btas.2013.6712697","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2013.6712697","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.699.4388","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.699.4388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www3.nd.edu/%7Ekwb/SgroiEtAlBTAS_2013.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1533303231","https://openalex.org/W1973614050","https://openalex.org/W1977566126","https://openalex.org/W1980732600","https://openalex.org/W1981291049","https://openalex.org/W1989474694","https://openalex.org/W2035830871","https://openalex.org/W2100332042","https://openalex.org/W2129312524","https://openalex.org/W2133295669","https://openalex.org/W2136808691","https://openalex.org/W2789848387","https://openalex.org/W2951293267"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W2143413548","https://openalex.org/W1969219540","https://openalex.org/W2098693229","https://openalex.org/W2384651879"],"abstract_inverted_index":{"The":[0,39,52,65,114],"Strong,":[1],"Neutral,":[2],"or":[3],"Weak":[4,66],"Face":[5,106],"Impostor":[6],"Pairs":[7],"problem":[8],"was":[9],"generated":[10],"to":[11,48,74,88],"explore":[12],"the":[13,32,81,90,97,105,128,133],"causes":[14,135],"and":[15,80,131],"impact":[16,127],"of":[17,25,83,92,100,116,124,136,142],"impostor":[18,33,125,138],"face":[19],"pairs":[20,44,57,70,139],"that":[21,45,58,71,121],"span":[22],"varying":[23,122],"strengths":[24],"scores.":[26],"We":[27],"develop":[28],"three":[29,94],"partitions":[30,95],"within":[31],"distribution":[34],"for":[35],"a":[36],"given":[37],"algorithm.":[38],"Strong":[40],"partition":[41,54,67],"contains":[42,55,68],"image":[43,56,69],"are":[46,59,72,140],"easy":[47],"categorize":[49],"as":[50,63],"impostors.":[51,64],"Neutral":[53],"less":[60],"easily":[61],"categorized":[62],"likely":[73],"cause":[75],"false":[76],"positives.":[77],"Three":[78],"algorithms,":[79],"fusion":[82],"their":[84],"scores,":[85],"were":[86],"used":[87],"analyze":[89],"performance":[91,130],"these":[93,117],"using":[96],"same":[98],"set":[99],"authentic":[101],"scores":[102,126],"employed":[103],"in":[104],"Recognition":[107],"Vendor":[108],"Test":[109],"(FRVT)":[110],"2006":[111],"Challenge":[112],"Dataset.":[113],"results":[115],"experiments":[118],"provide":[119],"evidence":[120],"degrees":[123],"overall":[129],"thus":[132],"underlying":[134],"weak":[137],"worthy":[141],"further":[143],"exploration.":[144]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
