{"id":"https://openalex.org/W2115210416","doi":"https://doi.org/10.1109/icassp.2006.1660310","title":"Class Dependent Kernel Discrete Cosine Transform Features for Enhanced Holistic Face Recognition in FRGC-II","display_name":"Class Dependent Kernel Discrete Cosine Transform Features for Enhanced Holistic Face Recognition in FRGC-II","publication_year":2006,"publication_date":"2006-08-02","ids":{"openalex":"https://openalex.org/W2115210416","doi":"https://doi.org/10.1109/icassp.2006.1660310","mag":"2115210416"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2006.1660310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings","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/A5057959136","display_name":"Marios Savvides","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M. Savvides","raw_affiliation_strings":["ECE Department, Carnegie Mellon University, USA","Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ"],"affiliations":[{"raw_affiliation_string":"ECE Department, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102266206","display_name":"Jingu Heo","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingu Heo","raw_affiliation_strings":["ECE Department, Carnegie Mellon University, USA","Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ"],"affiliations":[{"raw_affiliation_string":"ECE Department, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022968559","display_name":"Ramzi Abiantun","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Abiantun","raw_affiliation_strings":["ECE Department, Carnegie Mellon University, USA","Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ"],"affiliations":[{"raw_affiliation_string":"ECE Department, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100831521","display_name":"Chunyan Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunyan Xie","raw_affiliation_strings":["ECE Department, Carnegie Mellon University, USA","Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ"],"affiliations":[{"raw_affiliation_string":"ECE Department, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055345322","display_name":"B. V. K. Vijaya Kumar","orcid":"https://orcid.org/0000-0001-7126-6381"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"B.V.K.V. Kumar","raw_affiliation_strings":["ECE Department, Carnegie Mellon University, USA","Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ"],"affiliations":[{"raw_affiliation_string":"ECE Department, Carnegie Mellon University, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5057959136"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.5572,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.83945044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2","issue":null,"first_page":"II","last_page":"185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9973999857902527,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9973999857902527,"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/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.8554109334945679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.73701012134552},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.7006891965866089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6490039825439453},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6388363838195801},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5795354247093201},{"id":"https://openalex.org/keywords/lapped-transform","display_name":"Lapped transform","score":0.5365701913833618},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5321722626686096},{"id":"https://openalex.org/keywords/face-recognition-grand-challenge","display_name":"Face Recognition Grand Challenge","score":0.5178711414337158},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.49162036180496216},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.48679277300834656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4749841094017029},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4230906665325165},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4101705849170685},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.3141656219959259},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23673519492149353},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15654712915420532},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.1514343023300171}],"concepts":[{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.8554109334945679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73701012134552},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.7006891965866089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6490039825439453},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6388363838195801},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5795354247093201},{"id":"https://openalex.org/C91458471","wikidata":"https://www.wikidata.org/wiki/Q17096468","display_name":"Lapped transform","level":5,"score":0.5365701913833618},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5321722626686096},{"id":"https://openalex.org/C191070858","wikidata":"https://www.wikidata.org/wiki/Q5428343","display_name":"Face Recognition Grand Challenge","level":5,"score":0.5178711414337158},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.49162036180496216},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.48679277300834656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4749841094017029},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4230906665325165},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4101705849170685},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.3141656219959259},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23673519492149353},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15654712915420532},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.1514343023300171},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2006.1660310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660310","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings","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":12,"referenced_works":["https://openalex.org/W854322902","https://openalex.org/W2100115174","https://openalex.org/W2103971661","https://openalex.org/W2105594236","https://openalex.org/W2121647436","https://openalex.org/W2135346934","https://openalex.org/W2137659841","https://openalex.org/W2138451337","https://openalex.org/W2156909104","https://openalex.org/W2162419281","https://openalex.org/W6675924963","https://openalex.org/W6683908093"],"related_works":["https://openalex.org/W2258231948","https://openalex.org/W2162505377","https://openalex.org/W2094583657","https://openalex.org/W2115252864","https://openalex.org/W2112852877","https://openalex.org/W2128618986","https://openalex.org/W2119239074","https://openalex.org/W2111266495","https://openalex.org/W2133833176","https://openalex.org/W2106400387"],"abstract_inverted_index":{"Face":[0,68],"recognition":[1,39,55],"is":[2,43,87,149],"one":[3],"of":[4,77,165],"the":[5,23,27,33,53,67,88,97,122,141,155,175],"least":[6,28],"intrusive":[7],"biometric":[8],"modalities":[9],"that":[10,137],"can":[11],"be":[12],"used":[13],"to":[14,35],"identify":[15],"individuals":[16],"from":[17,66],"surveillance":[18],"video.":[19],"In":[20,46],"such":[21,41],"scenarios":[22,42],"users":[24],"are":[25],"under":[26],"co-operative":[29],"conditions":[30,95],"and":[31,91,133],"thus":[32],"ability":[34],"perform":[36],"robust":[37],"face":[38,54],"in":[40,93,140,154,179],"very":[44],"challenging.":[45],"this":[47],"paper":[48],"we":[49,134],"focus":[50,82],"on":[51,57,83],"improving":[52],"performance":[56,123],"a":[58,110,126,162],"large":[59],"database":[60],"with":[61],"over":[62],"36,000":[63],"facial":[64],"images":[65],"Recognition":[69],"Grand":[70],"Challenge":[71],"Phase-II":[72],"data":[73],"collected":[74],"by":[75,138,177],"University":[76],"Notre":[78],"Dame.":[79],"We":[80,108],"particularly":[81],"Experiment":[84],"4":[85],"which":[86,120,159],"most":[89],"challenging":[90],"captured":[92],"uncontrolled":[94],"where":[96],"baseline":[98,176],"PCA":[99],"algorithm":[100],"yields":[101,161],"12%":[102],"verification":[103,128,163,180],"rate":[104,129,164,181],"at":[105,130,167],"0.1%":[106,131,168],"FAR.":[107,169],"propose":[109],"novel":[111],"approach":[112],"using":[113],"class-dependent":[114],"kernel":[115],"discrete":[116],"cosine":[117],"transform":[118,143],"features":[119,148],"improves":[121],"significantly":[124],"yielding":[125],"91.33%":[127],"FAR,":[132],"also":[135],"show":[136],"working":[139,153],"DCT":[142],"domain":[144,158],"for":[145],"obtaining":[146],"non-linear":[147],"more":[150],"optimal":[151],"than":[152],"original":[156],"spatial-pixel":[157],"only":[160],"85%":[166],"Thus":[170],"our":[171],"proposed":[172],"method":[173],"outperforms":[174],"79.33%":[178],"@0.1%":[182],"False":[183],"Acceptance":[184],"Rate.":[185]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2012,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
