{"id":"https://openalex.org/W2401664211","doi":"https://doi.org/10.1109/wacv.2016.7477689","title":"Learning a structured dictionary for video-based face recognition","display_name":"Learning a structured dictionary for video-based face recognition","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2401664211","doi":"https://doi.org/10.1109/wacv.2016.7477689","mag":"2401664211"},"language":"en","primary_location":{"id":"doi:10.1109/wacv.2016.7477689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2016.7477689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Winter Conference on Applications of Computer Vision (WACV)","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/A5102918211","display_name":"Hongyu Xu","orcid":"https://orcid.org/0000-0002-9075-2307"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongyu Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072742668","display_name":"Jingjing Zheng","orcid":"https://orcid.org/0000-0003-1955-5308"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingjing Zheng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085657325","display_name":"Azadeh Alavi","orcid":"https://orcid.org/0000-0002-9565-217X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Azadeh Alavi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102762707","display_name":"Rama Chellappa","orcid":"https://orcid.org/0000-0002-7638-1650"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rama Chellappa","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0141,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.93313784,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"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/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"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/T11448","display_name":"Face recognition and analysis","score":0.9944000244140625,"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/computer-science","display_name":"Computer science","score":0.8143243193626404},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.7993866205215454},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7858591079711914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7484331130981445},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6483967304229736},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5543069839477539},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.549426257610321},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.5258194208145142},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5243873000144958},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42121607065200806},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35027140378952026},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.24602475762367249},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10591185092926025}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8143243193626404},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.7993866205215454},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7858591079711914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7484331130981445},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6483967304229736},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5543069839477539},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.549426257610321},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.5258194208145142},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5243873000144958},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42121607065200806},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35027140378952026},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.24602475762367249},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10591185092926025},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv.2016.7477689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2016.7477689","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320312530","display_name":"Office of the Director of National Intelligence","ror":"https://ror.org/01v3fsc55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W129703402","https://openalex.org/W198330749","https://openalex.org/W1175065802","https://openalex.org/W1506778248","https://openalex.org/W1550054889","https://openalex.org/W1589921458","https://openalex.org/W1607768360","https://openalex.org/W1814598697","https://openalex.org/W1900408618","https://openalex.org/W1922045146","https://openalex.org/W1928812244","https://openalex.org/W1996939238","https://openalex.org/W2019464758","https://openalex.org/W2021340975","https://openalex.org/W2022398315","https://openalex.org/W2027805700","https://openalex.org/W2035746673","https://openalex.org/W2043569121","https://openalex.org/W2066986622","https://openalex.org/W2068163954","https://openalex.org/W2084269393","https://openalex.org/W2084716923","https://openalex.org/W2097622337","https://openalex.org/W2100549954","https://openalex.org/W2110599581","https://openalex.org/W2120100419","https://openalex.org/W2120453412","https://openalex.org/W2122691893","https://openalex.org/W2134849720","https://openalex.org/W2137894166","https://openalex.org/W2144093206","https://openalex.org/W2145962650","https://openalex.org/W2157092301","https://openalex.org/W2157785665","https://openalex.org/W2160547390","https://openalex.org/W2160933580","https://openalex.org/W2161259116","https://openalex.org/W2162813111","https://openalex.org/W2169560406","https://openalex.org/W2331501241","https://openalex.org/W2951085447","https://openalex.org/W3021189487","https://openalex.org/W3097096317","https://openalex.org/W3105710301","https://openalex.org/W4285719527","https://openalex.org/W6605295242","https://openalex.org/W6608120278","https://openalex.org/W6627656566","https://openalex.org/W6635248833","https://openalex.org/W6636193568","https://openalex.org/W6659319144","https://openalex.org/W6675164516","https://openalex.org/W6676305975","https://openalex.org/W6678230916","https://openalex.org/W6680266532","https://openalex.org/W6680889708","https://openalex.org/W6683142446","https://openalex.org/W6683756719","https://openalex.org/W6684006261"],"related_works":["https://openalex.org/W2045881363","https://openalex.org/W2161305109","https://openalex.org/W2509955295","https://openalex.org/W2574002037","https://openalex.org/W1576854369","https://openalex.org/W4295805486","https://openalex.org/W3137366742","https://openalex.org/W1828907538","https://openalex.org/W2783701116","https://openalex.org/W1270326974"],"abstract_inverted_index":{"In":[0],"this":[1,102],"paper,":[2],"we":[3,27,53],"propose":[4],"a":[5,68],"structured":[6,92,113],"dictionary":[7,29,46],"learning":[8,30],"framework":[9],"for":[10],"video-based":[11,119],"face":[12,40,63,120],"recognition.":[13],"We":[14],"discover":[15,90],"the":[16,36,57,62,72,81,84,98],"invariant":[17,37,91],"structural":[18],"information":[19,93],"from":[20,75,94],"different":[21,76,95],"videos":[22,96],"of":[23,39,60,97],"each":[24],"subject.":[25,100],"Specifically,":[26],"employ":[28],"and":[31,50],"low-rank":[32,82],"approximation":[33],"to":[34,70,89,110],"preserve":[35],"structure":[38],"images":[41,64],"in":[42],"videos.":[43,77],"The":[44],"learned":[45],"is":[47,87,108],"both":[48],"discriminative":[49],"reconstructive.":[51],"Thus,":[52],"not":[54],"only":[55],"minimize":[56],"reconstruction":[58],"error":[59],"all":[61],"but":[65],"also":[66],"encourage":[67],"sub-dictionary":[69],"represent":[71],"corresponding":[73],"subject":[74],"Moreover,":[78],"by":[79],"introducing":[80],"approximation,":[83],"proposed":[85],"method":[86],"able":[88],"same":[99],"To":[101],"end,":[103],"an":[104],"efficient":[105],"alternating":[106],"algorithm":[107],"employed":[109],"learn":[111],"our":[112,125],"dictionary.":[114],"Extensive":[115],"experiments":[116],"on":[117],"three":[118],"recognition":[121],"databases":[122],"show":[123],"that":[124],"approach":[126],"outperforms":[127],"several":[128],"state-of-the-art":[129],"methods.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}