{"id":"https://openalex.org/W2732025305","doi":"https://doi.org/10.1109/fg.2017.36","title":"EPAT: Euclidean Perturbation Analysis and Transform - An Agnostic Data Adaptation Framework for Improving Facial Landmark Detectors","display_name":"EPAT: Euclidean Perturbation Analysis and Transform - An Agnostic Data Adaptation Framework for Improving Facial Landmark Detectors","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2732025305","doi":"https://doi.org/10.1109/fg.2017.36","mag":"2732025305"},"language":"en","primary_location":{"id":"doi:10.1109/fg.2017.36","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2017.36","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 12th IEEE International Conference on Automatic Face &amp; Gesture Recognition (FG 2017)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100668826","display_name":"Yue Wu","orcid":"https://orcid.org/0000-0003-0126-3614"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Wu","raw_affiliation_strings":["Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","Information Sciences Institute, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Information Sciences Institute, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028776484","display_name":"Wael AbdAlmageed","orcid":"https://orcid.org/0000-0002-8320-8530"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wael AbdAlmageed","raw_affiliation_strings":["Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","Information Sciences Institute, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Information Sciences Institute, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046697900","display_name":"Stephen Rawls","orcid":"https://orcid.org/0000-0001-8716-2528"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephen Rawls","raw_affiliation_strings":["Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","Information Sciences Institute, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Information Sciences Institute, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066184920","display_name":"Prem Natarajan","orcid":"https://orcid.org/0000-0002-4386-6651"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Premkumar Natarajan","raw_affiliation_strings":["Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","Information Sciences Institute, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inf. Sci. Inst., Univ. of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Information Sciences Institute, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05557953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"222","last_page":"229"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":1.0,"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":1.0,"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":0.9922999739646912,"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/T10828","display_name":"Biometric Identification and Security","score":0.9902999997138977,"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/landmark","display_name":"Landmark","score":0.9161142706871033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6675082445144653},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6214720010757446},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5915964841842651},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5793107151985168},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.536662220954895},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4837648868560791},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.4620479941368103},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4481988847255707},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.42044273018836975},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2668739855289459},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0796041488647461}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.9161142706871033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6675082445144653},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6214720010757446},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5915964841842651},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5793107151985168},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.536662220954895},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4837648868560791},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.4620479941368103},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4481988847255707},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.42044273018836975},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2668739855289459},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0796041488647461},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fg.2017.36","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2017.36","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 12th IEEE International Conference on Automatic Face &amp; Gesture Recognition (FG 2017)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W975491072","https://openalex.org/W1480376833","https://openalex.org/W1530071549","https://openalex.org/W1796263212","https://openalex.org/W1915668717","https://openalex.org/W1949778830","https://openalex.org/W1963599662","https://openalex.org/W1990937109","https://openalex.org/W2006902452","https://openalex.org/W2015227583","https://openalex.org/W2015229219","https://openalex.org/W2047508432","https://openalex.org/W2058961190","https://openalex.org/W2087681821","https://openalex.org/W2103913182","https://openalex.org/W2128053425","https://openalex.org/W2143350951","https://openalex.org/W2151802865","https://openalex.org/W2157285372","https://openalex.org/W2307523691","https://openalex.org/W2431345793","https://openalex.org/W2963483939","https://openalex.org/W6625299338","https://openalex.org/W6631826233","https://openalex.org/W6662335928"],"related_works":["https://openalex.org/W2090152127","https://openalex.org/W1965169884","https://openalex.org/W3125580510","https://openalex.org/W2008939113","https://openalex.org/W2033213447","https://openalex.org/W14679004","https://openalex.org/W1566651525","https://openalex.org/W2977652649","https://openalex.org/W2318206461","https://openalex.org/W37157938"],"abstract_inverted_index":{"We":[0,116],"propose":[1],"EPAT,":[2,33],"(Euclidean":[3],"Perturbation":[4],"Analysis":[5],"and":[6,90,100,107,138,155,176],"Transform)":[7],"a":[8,34,42,129,139,143,180],"novel":[9],"unsupervised":[10],"adaptation":[11,146],"approach":[12],"for":[13,94,141],"improving":[14],"the":[15,24,67,76,86,103,108,111,132,135,159,172,190],"accuracy":[16,188],"of":[17,26,44,66,110,122,131,134,158],"any":[18],"facial":[19,60,123],"landmark":[20,27,54,113,161,169],"detector":[21,55],"by":[22],"characterizing":[23],"stability":[25,133],"prediction":[28,106],"on":[29,62,171,189],"test":[30,35,68,154],"images.":[31,50],"In":[32],"image":[36],"is":[37,56,126,164],"transformed":[38,97],"several":[39,48],"times":[40],"using":[41,166],"set":[43],"Euclidean":[45],"transforms,":[46],"producing":[47],"perturbed":[49,64],"The":[51],"black":[52],"box":[53],"used":[57,127],"to":[58,75,81,85,184],"find":[59],"landmarks":[61,78,137],"each":[63],"version":[65],"image.":[69,88],"Subsequently,":[70],"inverse":[71],"transforms":[72],"are":[73,92],"applied":[74],"corresponding":[77],"in":[79],"order":[80],"map":[82],"them":[83],"back":[84],"original":[87],"Mean":[89,99],"variance":[91,101,120],"calculated":[93],"all":[95],"inversely":[96],"detection.":[98],"represent":[102],"new":[104],"ensemble":[105],"sensitivity":[109],"underlying":[112,160],"detector,":[114],"respectively.":[115],"also":[117,177],"introduce":[118],"affine":[119],"(AV)":[121],"landmarks.":[124],"AV":[125],"as":[128],"measure":[130],"predicted":[136],"criterion":[140],"selecting":[142],"good":[144],"data":[145,157],"model":[147],"which":[148],"effectively":[149],"addresses":[150],"potential":[151],"mismatches":[152],"between":[153],"training":[156],"detector.":[162],"EPAT":[163],"evaluated":[165],"four":[167],"state-of-the-art":[168],"detectors":[170],"standard":[173],"300W":[174],"dataset":[175],"incorporated":[178],"into":[179],"face":[181],"recognition":[182,187],"pipeline":[183],"show":[185],"improved":[186],"challenging":[191],"IJB-A":[192],"dataset.":[193]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
