{"id":"https://openalex.org/W2751795017","doi":"https://doi.org/10.1109/icmew.2017.8026269","title":"A novel and robust face clustering method via adaptive difference dictionary","display_name":"A novel and robust face clustering method via adaptive difference dictionary","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2751795017","doi":"https://doi.org/10.1109/icmew.2017.8026269","mag":"2751795017"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2017.8026269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2017.8026269","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","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/A5112316599","display_name":"Jiaxiang Ren","orcid":"https://orcid.org/0009-0007-7363-5428"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaxiang Ren","raw_affiliation_strings":["Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035948567","display_name":"Shengjie Zhao","orcid":"https://orcid.org/0000-0002-6109-2522"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengjie Zhao","raw_affiliation_strings":["Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101686926","display_name":"Kai Yang","orcid":"https://orcid.org/0000-0002-9966-1380"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Yang","raw_affiliation_strings":["Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Embedded System and Service Computing, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044381910","display_name":"Brian Nlong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brian Nlong Zhao","raw_affiliation_strings":["International Division, Shanghai High School, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"International Division, Shanghai High School, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112316599"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46233334,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"627","last_page":"632"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994000196456909,"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":0.9994000196456909,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9865000247955322,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8114266395568848},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7486693859100342},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.651374101638794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6171674728393555},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6116413474082947},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6093412041664124},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5704056620597839},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5689133405685425},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.548395037651062},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4790124297142029},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.47038331627845764},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4696497321128845},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.44238829612731934},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4422683119773865},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.42118212580680847},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32187432050704956},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18106982111930847}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8114266395568848},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7486693859100342},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.651374101638794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6171674728393555},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6116413474082947},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6093412041664124},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5704056620597839},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5689133405685425},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.548395037651062},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4790124297142029},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.47038331627845764},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4696497321128845},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.44238829612731934},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4422683119773865},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.42118212580680847},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32187432050704956},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18106982111930847},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2017.8026269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2017.8026269","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","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":22,"referenced_works":["https://openalex.org/W1591385104","https://openalex.org/W1967825168","https://openalex.org/W1993962865","https://openalex.org/W2003217181","https://openalex.org/W2085261163","https://openalex.org/W2118154608","https://openalex.org/W2120100419","https://openalex.org/W2145152441","https://openalex.org/W2145962650","https://openalex.org/W2163808566","https://openalex.org/W2164278908","https://openalex.org/W2165874743","https://openalex.org/W2177347332","https://openalex.org/W2271263562","https://openalex.org/W2283717164","https://openalex.org/W2294644361","https://openalex.org/W2994340921","https://openalex.org/W3022380717","https://openalex.org/W4250657332","https://openalex.org/W4292363360","https://openalex.org/W6635552349","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W227974271","https://openalex.org/W1580457994","https://openalex.org/W1973963881","https://openalex.org/W2769045829","https://openalex.org/W2379945344","https://openalex.org/W2912726270","https://openalex.org/W2968737478","https://openalex.org/W88288160","https://openalex.org/W2185081213","https://openalex.org/W2761926807"],"abstract_inverted_index":{"High-dimensional":[0],"data":[1,20],"are":[2,57,106,145],"ubiquitous":[3],"in":[4,30,123],"most":[5],"real-world":[6],"research":[7],"areas,":[8],"such":[9,45],"as":[10,46],"machine":[11],"learning,":[12],"image":[13],"processing":[14],"and":[15,54,132,141,178],"so":[16],"on.":[17],"Actually,":[18],"high-dimensional":[19],"that":[21,96,157],"belong":[22],"to":[23,28,59,83,114,165,188],"the":[24,42,61,97,103,110,116,126,129,133,139,152,158],"same":[25],"classes":[26],"tend":[27],"gather":[29],"their":[31,55],"own":[32],"low-dimensional":[33],"subspaces.":[34],"Recently,":[35],"many":[36],"subspace":[37,62],"recovery":[38],"algorithms":[39],"based":[40,74],"on":[41,75,151,168],"sparse":[43],"representation":[44],"Sparse":[47,79],"Subspace":[48,80],"Clustering":[49,81],"(SSC),":[50],"Low-Rank":[51],"Representation":[52],"(LRR)":[53],"variants":[56],"proposed":[58,159],"address":[60],"clustering":[63,72,144,185],"problems.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68,108],"propose":[69],"a":[70],"novel":[71],"method":[73],"SSC,":[76,172],"called":[77],"Enhanced":[78],"(ESSC),":[82],"deal":[84],"with":[85,125,171,182],"complicated":[86],"face":[87,104,121,154,184],"images":[88,105,122],"under":[89,194],"variant":[90,98,195],"expressions,":[91,196],"illuminations":[92],"or":[93,100,198],"disguises.":[94],"Assuming":[95],"expressions":[99],"disguises":[101,197],"of":[102,120,128,138,143],"sharable,":[107],"introduce":[109],"adaptive":[111],"difference":[112],"dictionary":[113],"extend":[115],"simple":[117],"linear":[118],"combination":[119,127],"SSC":[124],"specific":[130],"features":[131],"common":[134],"features.":[135],"Thus":[136],"both":[137],"accuracy":[140,169],"generalization":[142],"improved":[146],"simultaneously.":[147],"The":[148],"experimental":[149],"results":[150],"AR":[153],"databases":[155],"show":[156],"ESSC":[160],"not":[161],"only":[162],"makes":[163],"up":[164],"9.0%":[166],"improvements":[167],"compared":[170],"but":[173],"also":[174],"is":[175],"more":[176],"robust":[177],"scalable":[179],"for":[180],"dealing":[181],"larger":[183],"problems":[186],"(up":[187],"400":[189],"samples":[190],"from":[191],"100":[192],"subjects)":[193],"illuminations.":[199]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}