{"id":"https://openalex.org/W2148036851","doi":"https://doi.org/10.1109/cvpr.2009.5206730","title":"Efficiently training a better visual detector with sparse eigenvectors","display_name":"Efficiently training a better visual detector with sparse eigenvectors","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2148036851","doi":"https://doi.org/10.1109/cvpr.2009.5206730","mag":"2148036851"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206730","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","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/A5083707053","display_name":"Sakrapee Paisitkriangkrai","orcid":null},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Sakrapee Paisitkriangkrai","raw_affiliation_strings":["NICTA, University of New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"NICTA, University of New South Wales, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006294869","display_name":"Chunhua Shen","orcid":"https://orcid.org/0000-0002-8648-8718"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chunhua Shen","raw_affiliation_strings":["NICTA, Australian National University, Australia"],"affiliations":[{"raw_affiliation_string":"NICTA, Australian National University, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100409994","display_name":"Jian Zhang","orcid":"https://orcid.org/0000-0002-7240-3541"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["NICTA, University of New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"NICTA, University of New South Wales, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5083707053"],"corresponding_institution_ids":["https://openalex.org/I31746571","https://openalex.org/I42894916"],"apc_list":null,"apc_paid":null,"fwci":1.1197,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82405745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1129","last_page":"1136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9944999814033508,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9884999990463257,"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/boosting","display_name":"Boosting (machine learning)","score":0.892615556716919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7434258460998535},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.7320221662521362},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7165912389755249},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6557714343070984},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5942751169204712},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.5402315855026245},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5067477822303772},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5009744167327881},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.475117027759552},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4705405831336975},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.46491414308547974},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4593953788280487},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4418785572052002},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42693397402763367},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.28660017251968384},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15296947956085205}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.892615556716919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7434258460998535},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.7320221662521362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7165912389755249},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6557714343070984},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5942751169204712},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.5402315855026245},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5067477822303772},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5009744167327881},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.475117027759552},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4705405831336975},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.46491414308547974},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4593953788280487},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4418785572052002},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42693397402763367},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.28660017251968384},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15296947956085205},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2009.5206730","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206730","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.715.5950","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.715.5950","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.adelaide.edu.au/%7Epaulp/publications/pubs/cvpr2009.pdf","raw_type":"text"},{"id":"pmh:oai:digital.library.adelaide.edu.au:2440/67405","is_oa":false,"landing_page_url":"http://hdl.handle.net/2440/67405","pdf_url":null,"source":{"id":"https://openalex.org/S4306401835","display_name":"Adelaide Research & Scholarship (AR&S) (University of Adelaide)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I5681781","host_organization_name":"The University of Adelaide","host_organization_lineage":["https://openalex.org/I5681781"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://dx.doi.org/10.1109/cvpr.2009.5206730","raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[],"funders":[{"id":"https://openalex.org/F4320315885","display_name":"Australian Government","ror":"https://ror.org/0314h5y94"},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1525410796","https://openalex.org/W1578080815","https://openalex.org/W1580049798","https://openalex.org/W1968290438","https://openalex.org/W1998938582","https://openalex.org/W2024046085","https://openalex.org/W2104577112","https://openalex.org/W2104955141","https://openalex.org/W2118373237","https://openalex.org/W2121275167","https://openalex.org/W2122352046","https://openalex.org/W2159548580","https://openalex.org/W2163194396","https://openalex.org/W2164251185","https://openalex.org/W2743477090","https://openalex.org/W3097096317","https://openalex.org/W6634569365","https://openalex.org/W6675785006","https://openalex.org/W6678078302","https://openalex.org/W6684226807"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W2385662756","https://openalex.org/W2585372724","https://openalex.org/W2241444561"],"abstract_inverted_index":{"Face":[0],"detection":[1,22,76],"plays":[2],"an":[3,53],"important":[4],"role":[5],"in":[6,117],"many":[7],"vision":[8],"applications.":[9],"Since":[10],"Viola":[11],"and":[12,73,110,138,151],"Jones":[13],"[1]":[14],"proposed":[15,134],"the":[16,31,104,111,118,133,156],"first":[17,38],"real-time":[18],"AdaBoost":[19,137],"based":[20],"object":[21,55,100,171],"system,":[23],"much":[24],"effort":[25],"has":[26],"been":[27],"spent":[28],"on":[29],"improving":[30],"boosting":[32,46,109],"method.":[33],"In":[34,57],"this":[35],"work,":[36],"we":[37,59,84],"show":[39],"that":[40,129,149,159],"feature":[41],"selection":[42],"methods":[43,158],"other":[44],"than":[45],"can":[47,160],"also":[48],"be":[49],"used":[50],"for":[51,69,165],"training":[52],"efficient":[54],"detector.":[56],"particular,":[58],"have":[60],"adopted":[61],"Greedy":[62,91],"Sparse":[63,92],"Linear":[64,93],"Discriminant":[65,94],"Analysis":[66,95],"(GSLDA)":[67],"[2]":[68],"its":[70,139],"computational":[71],"efficiency;":[72],"slightly":[74],"better":[75],"performance":[77],"is":[78],"achieved":[79],"compared":[80],"with":[81,132],"[1].":[82],"Moreover,":[83],"propose":[85],"a":[86,144],"new":[87],"technique,":[88],"termed":[89],"Boosted":[90],"(BGSLDA),":[96],"to":[97,147],"efficiently":[98],"train":[99],"detectors.":[101],"BGSLDA":[102,135],"exploits":[103],"sample":[105],"re-weighting":[106],"property":[107],"of":[108,114,120],"class-separability":[112],"criterion":[113],"GSLDA.":[115],"Experiments":[116],"domain":[119],"highly":[121],"skewed":[122],"data":[123,168],"distributions,":[124],"e.g.,":[125],"face":[126],"detection,":[127],"demonstrates":[128],"classifiers":[130],"trained":[131],"outperforms":[136],"variants.":[140],"This":[141],"finding":[142],"provides":[143],"significant":[145],"opportunity":[146],"argue":[148],"Adaboost":[150],"similar":[152],"approaches":[153],"are":[154],"not":[155],"only":[157],"achieve":[161],"high":[162,166],"classification":[163],"results":[164],"dimensional":[167],"such":[169],"as":[170],"detection.":[172]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}