{"id":"https://openalex.org/W4293236025","doi":"https://doi.org/10.1145/3531014","title":"Distance and Direction Based Deep Discriminant Metric Learning for Kinship Verification","display_name":"Distance and Direction Based Deep Discriminant Metric Learning for Kinship Verification","publication_year":2022,"publication_date":"2022-04-23","ids":{"openalex":"https://openalex.org/W4293236025","doi":"https://doi.org/10.1145/3531014"},"language":"en","primary_location":{"id":"doi:10.1145/3531014","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3531014","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-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/A5012689262","display_name":"Xiaoke Zhu","orcid":"https://orcid.org/0000-0002-0664-1832"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoke Zhu","raw_affiliation_strings":["Henan University, Kaifeng, China"],"raw_orcid":"https://orcid.org/0000-0002-0664-1832","affiliations":[{"raw_affiliation_string":"Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100616446","display_name":"Changlong Li","orcid":"https://orcid.org/0000-0001-6301-9866"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changlong Li","raw_affiliation_strings":["Henan University, Kaifeng, China"],"raw_orcid":"https://orcid.org/0000-0001-6301-9866","affiliations":[{"raw_affiliation_string":"Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103096202","display_name":"Xiaopan Chen","orcid":"https://orcid.org/0000-0002-2766-9367"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaopan Chen","raw_affiliation_strings":["Henan University, Kaifeng, China"],"raw_orcid":"https://orcid.org/0000-0002-2766-9367","affiliations":[{"raw_affiliation_string":"Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390716","display_name":"Xinyu Zhang","orcid":"https://orcid.org/0000-0002-9109-1889"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Zhang","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-9109-1889","affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029691902","display_name":"Xiao\u2010Yuan Jing","orcid":"https://orcid.org/0000-0002-0392-8475"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Yuan Jing","raw_affiliation_strings":["Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0392-8475","affiliations":[{"raw_affiliation_string":"Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8809,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.74133901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"19","issue":"1s","first_page":"1","last_page":"19"},"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":0.9811999797821045,"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":0.9728000164031982,"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/metric","display_name":"Metric (unit)","score":0.8015460968017578},{"id":"https://openalex.org/keywords/kinship","display_name":"Kinship","score":0.7894303202629089},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6705585718154907},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6666727066040039},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6591442227363586},{"id":"https://openalex.org/keywords/discriminant-function-analysis","display_name":"Discriminant function analysis","score":0.6591324806213379},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6356788277626038},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5856767892837524},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5645362138748169},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5251039266586304},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4772850573062897},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41543930768966675},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3931977450847626},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38527822494506836},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3186491131782532},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.07838582992553711}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.8015460968017578},{"id":"https://openalex.org/C144348335","wikidata":"https://www.wikidata.org/wiki/Q171318","display_name":"Kinship","level":2,"score":0.7894303202629089},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6705585718154907},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6666727066040039},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6591442227363586},{"id":"https://openalex.org/C41771347","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Discriminant function analysis","level":2,"score":0.6591324806213379},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6356788277626038},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5856767892837524},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5645362138748169},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5251039266586304},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4772850573062897},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41543930768966675},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3931977450847626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38527822494506836},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3186491131782532},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.07838582992553711},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3531014","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3531014","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1295009996","display_name":null,"funder_award_id":"62176069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4550463141","display_name":null,"funder_award_id":"62006070","funder_id":"https://openalex.org/F4320331088","funder_display_name":"Natural Science Foundation for Young Scientists of Shanxi Province"},{"id":"https://openalex.org/G491289108","display_name":null,"funder_award_id":"2019A1515011076","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6855927641","display_name":null,"funder_award_id":"202300410092 and 202300410093","funder_id":"https://openalex.org/F4320323845","funder_display_name":"Natural Science Foundation of Henan Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320323845","display_name":"Natural Science Foundation of Henan Province","ror":null},{"id":"https://openalex.org/F4320331088","display_name":"Natural Science Foundation for Young Scientists of Shanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1241252238","https://openalex.org/W1972014290","https://openalex.org/W1996337501","https://openalex.org/W2012783213","https://openalex.org/W2071207147","https://openalex.org/W2071330692","https://openalex.org/W2079742827","https://openalex.org/W2093993142","https://openalex.org/W2108909793","https://openalex.org/W2123619251","https://openalex.org/W2132886138","https://openalex.org/W2142431032","https://openalex.org/W2145773134","https://openalex.org/W2164322079","https://openalex.org/W2335788292","https://openalex.org/W2505321620","https://openalex.org/W2520903215","https://openalex.org/W2552765257","https://openalex.org/W2558333741","https://openalex.org/W2560835477","https://openalex.org/W2615497679","https://openalex.org/W2679426462","https://openalex.org/W2761999006","https://openalex.org/W2766372859","https://openalex.org/W2797200251","https://openalex.org/W2806332870","https://openalex.org/W2886356144","https://openalex.org/W2897151190","https://openalex.org/W2913071101","https://openalex.org/W2938731855","https://openalex.org/W2963842104","https://openalex.org/W2969336025","https://openalex.org/W2994455292","https://openalex.org/W3037574114","https://openalex.org/W3054638514","https://openalex.org/W3105535737","https://openalex.org/W3146675199","https://openalex.org/W3159280478","https://openalex.org/W3215141862"],"related_works":["https://openalex.org/W2353567328","https://openalex.org/W2146076056","https://openalex.org/W2380927352","https://openalex.org/W2339674921","https://openalex.org/W2156856390","https://openalex.org/W2157903613","https://openalex.org/W1968332688","https://openalex.org/W1560999061","https://openalex.org/W4293236025","https://openalex.org/W2793296642"],"abstract_inverted_index":{"Image-based":[0],"kinship":[1,53,77,152],"verification":[2,54],"is":[3,86,143,191],"an":[4],"important":[5],"task":[6],"in":[7,14,31,96,206,217],"computer":[8],"vision":[9],"and":[10,21,35,49,65,102,132,153,166,180],"has":[11],"many":[12],"applications":[13],"practice,":[15,162],"such":[16,104],"as":[17],"missing":[18],"children":[19],"search":[20],"family":[22],"album":[23],"construction,":[24],"among":[25],"others.":[26],"Due":[27],"to":[28,87,145,228],"the":[29,44,92,97,106,120,124,136,139,147,155,163,173,184,213,218,230,233,246],"differences":[30],"age,":[32],"gender,":[33],"expression":[34],"appearance,":[36],"there":[37],"usually":[38],"exists":[39],"a":[40,55,63,111,188,198],"large":[41,167,199],"discrepancy":[42],"between":[43,149,157,175],"facial":[45,98,176],"images":[46,99,150,158,177],"of":[47,82,91,100,178,223,232,248,253],"parent":[48,101,179],"child.":[50,181],"This":[51],"makes":[52],"challenging":[56],"task.":[57],"In":[58,161],"this":[59],"article,":[60],"we":[61],"propose":[62],"Distance":[64],"Direction":[66],"Based":[67],"Deep":[68],"Discriminant":[69],"Metric":[70],"Learning":[71],"(D":[72],"4":[73,84,117,209],"ML)":[74],"approach":[75,255],"for":[76],"verification.":[78],"The":[79],"basic":[80],"idea":[81],"D":[83,116,208],"ML":[85,118,210],"make":[88],"full":[89],"use":[90],"discriminant":[93,125],"information":[94,126],"contained":[95],"child":[103],"that":[105,194],"network":[107],"can":[108,256],"learn":[109],"more":[110],"discriminating":[112],"distance":[113,148,156,174,200],"metric.":[114,235],"Specifically,":[115],"learns":[119],"metric":[121,185],"by":[122],"utilizing":[123],"from":[127,187],"two":[128,195],"perspectives:":[129],"distance-based":[130,137,189],"perspective":[131,190],"direction-based":[133,214],"perspective.":[134],"From":[135],"perspective,":[138],"designed":[140],"loss":[141,215,224],"function":[142,216,225],"used":[144],"minimize":[146],"having":[151],"maximize":[154],"without":[159],"kinship.":[160],"gender":[164],"difference":[165],"age":[168],"gap":[169],"may":[170,201],"significantly":[171],"increase":[172],"Therefore,":[182],"learning":[183],"only":[186],"insufficient.":[192],"Considering":[193],"vectors":[196],"with":[197,203],"appear":[202],"high":[204],"similarity":[205],"direction,":[207],"also":[211],"employs":[212],"training":[219],"process.":[220],"Both":[221],"kinds":[222],"work":[226],"together":[227],"improve":[229],"discriminability":[231],"learned":[234],"Experimental":[236],"results":[237],"on":[238],"four":[239],"small":[240],"size":[241],"publicly":[242],"available":[243],"datasets":[244],"demonstrate":[245],"effectiveness":[247],"our":[249,254],"approach.":[250],"Source":[251],"code":[252],"be":[257],"found":[258],"at":[259],"https://github.com/lclhenu/D4ML":[260],".":[261]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}