{"id":"https://openalex.org/W2160735653","doi":"https://doi.org/10.1109/icip.2009.5413674","title":"Fea-Accu cascade for face detection","display_name":"Fea-Accu cascade for face detection","publication_year":2009,"publication_date":"2009-11-01","ids":{"openalex":"https://openalex.org/W2160735653","doi":"https://doi.org/10.1109/icip.2009.5413674","mag":"2160735653"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2009.5413674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","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/A5041252235","display_name":"Shengye Yan","orcid":"https://orcid.org/0000-0003-3583-0146"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengye Yan","raw_affiliation_strings":["Chinese Academy and Sciences, Beijing, China","Institute of Computing Technology, Digital Media Research Center, Chinese Academy and Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy and Sciences, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Institute of Computing Technology, Digital Media Research Center, Chinese Academy and Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050297728","display_name":"Shiguang Shan","orcid":"https://orcid.org/0000-0002-8348-392X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiguang Shan","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083420537","display_name":"Xilin Chen","orcid":"https://orcid.org/0000-0003-3024-4404"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xilin Chen","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing, Chinese Academy and Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing, Chinese Academy and Sciences, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101523804","display_name":"Wen Gao","orcid":"https://orcid.org/0000-0001-8894-1806"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Gao","raw_affiliation_strings":["Institute of Computing Technology, Digital Media Research Center, Chinese Academy and Sciences, Beijing, China","School of EE & CS, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Digital Media Research Center, Chinese Academy and Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]},{"raw_affiliation_string":"School of EE & CS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1217","last_page":"1220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9854999780654907,"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/cascade","display_name":"Cascade","score":0.8810977339744568},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7790981531143188},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7117151021957397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6876441240310669},{"id":"https://openalex.org/keywords/cascading-classifiers","display_name":"Cascading classifiers","score":0.634422779083252},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5405437350273132},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45846354961395264},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4488605856895447},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42273083329200745},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.41582009196281433},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.23185038566589355},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11102038621902466}],"concepts":[{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.8810977339744568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7790981531143188},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7117151021957397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6876441240310669},{"id":"https://openalex.org/C40651066","wikidata":"https://www.wikidata.org/wiki/Q5048220","display_name":"Cascading classifiers","level":4,"score":0.634422779083252},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5405437350273132},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45846354961395264},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4488605856895447},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42273083329200745},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.41582009196281433},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.23185038566589355},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11102038621902466},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2009.5413674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.360.2587","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.360.2587","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.jdl.ac.cn/doc/2009/ICIP09_Fea-Accu Cascade For Face Detection.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1493269421","https://openalex.org/W1877382520","https://openalex.org/W1989192414","https://openalex.org/W2032210760","https://openalex.org/W2106309274","https://openalex.org/W2114758632","https://openalex.org/W2115763357","https://openalex.org/W2124351082","https://openalex.org/W2133860751","https://openalex.org/W2138560582","https://openalex.org/W2140274257","https://openalex.org/W2147474239","https://openalex.org/W2154376992","https://openalex.org/W2155511848","https://openalex.org/W2159686933","https://openalex.org/W2164598857","https://openalex.org/W2170065295","https://openalex.org/W2170110077","https://openalex.org/W2217896605","https://openalex.org/W4232222670","https://openalex.org/W4244104295","https://openalex.org/W4244952642","https://openalex.org/W4248235699","https://openalex.org/W6629580165","https://openalex.org/W6639399000","https://openalex.org/W6677171743","https://openalex.org/W6679933893","https://openalex.org/W6682857711"],"related_works":["https://openalex.org/W2388864896","https://openalex.org/W2032805221","https://openalex.org/W2407804800","https://openalex.org/W2982026416","https://openalex.org/W2078677419","https://openalex.org/W2913388591","https://openalex.org/W2117265009","https://openalex.org/W2953702789","https://openalex.org/W2101217650","https://openalex.org/W2779991293"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"unloading":[2],"the":[3,9,29,39,46,60,78,83,103],"high":[4],"training":[5,104],"time":[6],"burden":[7],"of":[8,31,45,82],"popular":[10],"cascaded":[11,47],"classifier,":[12,54],"in":[13,117],"this":[14],"paper,":[15],"a":[16],"novel":[17],"cascade":[18,22,27],"structure":[19],"called":[20],"Fea-Accu":[21,26],"is":[23,87],"proposed.":[24],"In":[25,49],"training,":[28],"times":[30],"feature":[32],"selection":[33],"are":[34,68],"largely":[35,101],"reduced":[36],"by":[37,64],"enhancing":[38],"correlation":[40],"among":[41],"different":[42],"stage":[43,53,66],"classifiers":[44,67],"classifier.":[48],"detail,":[50],"for":[51],"each":[52],"before":[55],"selecting":[56],"new":[57,72],"features":[58,61],"out,":[59],"selected":[62],"out":[63],"previous":[65],"reused":[69],"through":[70],"creating":[71],"corresponding":[73],"weak":[74],"classifiers.":[75],"To":[76],"verify":[77],"efficiency":[79],"and":[80],"effectiveness":[81],"proposed":[84],"method,":[85],"experiment":[86],"designed":[88],"on":[89],"frontal":[90,107],"face":[91,108],"detection":[92],"problem.":[93],"The":[94],"experimental":[95],"results":[96],"show":[97],"that":[98],"it":[99],"can":[100,114],"reduce":[102],"time.":[105],"A":[106],"detector":[109],"with":[110],"state-of-the-art":[111],"classification":[112],"performance":[113],"be":[115],"learned":[116],"less":[118],"than":[119],"10":[120],"hours.":[121]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}