{"id":"https://openalex.org/W2021340975","doi":"https://doi.org/10.1109/cvpr.2011.5995500","title":"Sparse approximated nearest points for image set classification","display_name":"Sparse approximated nearest points for image set classification","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2021340975","doi":"https://doi.org/10.1109/cvpr.2011.5995500","mag":"2021340975"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2011.5995500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research-repository.uwa.edu.au/en/publications/854761e3-9034-4663-a626-f666381d6b21","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102837904","display_name":"Yiqun Hu","orcid":"https://orcid.org/0000-0001-9157-7865"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yiqun Hu","raw_affiliation_strings":["School of Computer Science & Software Engineering, University of Western Australia, Australia","School of Computer Science & Software Engineering, The University of Western Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science & Software Engineering, University of Western Australia, Australia","institution_ids":["https://openalex.org/I177877127"]},{"raw_affiliation_string":"School of Computer Science & Software Engineering, The University of Western Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089986388","display_name":"Ajmal Mian","orcid":"https://orcid.org/0000-0002-5206-3842"},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ajmal S. Mian","raw_affiliation_strings":["School of Computer Science & Software Engineering, University of Western Australia, Australia","School of Computer Science & Software Engineering, The University of Western Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science & Software Engineering, University of Western Australia, Australia","institution_ids":["https://openalex.org/I177877127"]},{"raw_affiliation_string":"School of Computer Science & Software Engineering, The University of Western Australia","institution_ids":["https://openalex.org/I177877127"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108791399","display_name":"Robyn Owens","orcid":null},"institutions":[{"id":"https://openalex.org/I177877127","display_name":"The University of Western Australia","ror":"https://ror.org/047272k79","country_code":"AU","type":"education","lineage":["https://openalex.org/I177877127"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Robyn Owens","raw_affiliation_strings":["School of Computer Science & Software Engineering, University of Western Australia, Australia","School of Computer Science & Software Engineering, The University of Western Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science & Software Engineering, University of Western Australia, Australia","institution_ids":["https://openalex.org/I177877127"]},{"raw_affiliation_string":"School of Computer Science & Software Engineering, The University of Western Australia","institution_ids":["https://openalex.org/I177877127"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177877127"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":221,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"121","last_page":"128"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9919999837875366,"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/T10057","display_name":"Face and Expression Recognition","score":0.9890999794006348,"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/affine-transformation","display_name":"Affine transformation","score":0.7273201942443848},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6097329258918762},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5892772078514099},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5786030292510986},{"id":"https://openalex.org/keywords/affine-hull","display_name":"Affine hull","score":0.5667064189910889},{"id":"https://openalex.org/keywords/convex-hull","display_name":"Convex hull","score":0.5593598484992981},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5268158912658691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4700944125652313},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4666939377784729},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4661952555179596},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4521227180957794},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43502679467201233},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4266259968280792},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3950478136539459},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.36011913418769836},{"id":"https://openalex.org/keywords/affine-space","display_name":"Affine space","score":0.15013539791107178}],"concepts":[{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.7273201942443848},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6097329258918762},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5892772078514099},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5786030292510986},{"id":"https://openalex.org/C112128483","wikidata":"https://www.wikidata.org/wiki/Q382504","display_name":"Affine hull","level":4,"score":0.5667064189910889},{"id":"https://openalex.org/C206194317","wikidata":"https://www.wikidata.org/wiki/Q1138624","display_name":"Convex hull","level":3,"score":0.5593598484992981},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5268158912658691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4700944125652313},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4666939377784729},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4661952555179596},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4521227180957794},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43502679467201233},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4266259968280792},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3950478136539459},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.36011913418769836},{"id":"https://openalex.org/C173110770","wikidata":"https://www.wikidata.org/wiki/Q382698","display_name":"Affine space","level":3,"score":0.15013539791107178},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2011.5995500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/854761e3-9034-4663-a626-f666381d6b21","is_oa":true,"landing_page_url":"https://research-repository.uwa.edu.au/en/publications/854761e3-9034-4663-a626-f666381d6b21","pdf_url":"https://research-repository.uwa.edu.au/en/publications/854761e3-9034-4663-a626-f666381d6b21","source":{"id":"https://openalex.org/S4306402523","display_name":"UWA Profiles and Research Repository (University of Western Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Hu , Y , Mian , A & Owens , R 2011 , Sparse approximated nearest points for image set classification . in 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE, Institute of Electrical and Electronics Engineers , USA , pp. 121-128 , 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , Colorado Springs , Colorado , United States , 20/06/11 . https://doi.org/10.1109/CVPR.2011.5995500","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.221.3299","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.3299","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.csse.uwa.edu.au/%7Eajmal/papers/cvpr2011_yiqun.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:publications/854761e3-9034-4663-a626-f666381d6b21","is_oa":true,"landing_page_url":"https://research-repository.uwa.edu.au/en/publications/854761e3-9034-4663-a626-f666381d6b21","pdf_url":"https://research-repository.uwa.edu.au/en/publications/854761e3-9034-4663-a626-f666381d6b21","source":{"id":"https://openalex.org/S4306402523","display_name":"UWA Profiles and Research Repository (University of Western Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Hu , Y , Mian , A & Owens , R 2011 , Sparse approximated nearest points for image set classification . in 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE, Institute of Electrical and Electronics Engineers , USA , pp. 121-128 , 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , Colorado Springs , Colorado , United States , 20/06/11 . https://doi.org/10.1109/CVPR.2011.5995500","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332603","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2021340975.pdf","grobid_xml":"https://content.openalex.org/works/W2021340975.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1506778248","https://openalex.org/W1550365753","https://openalex.org/W1550919879","https://openalex.org/W1552704115","https://openalex.org/W1596150838","https://openalex.org/W1820849028","https://openalex.org/W1996939238","https://openalex.org/W2025341678","https://openalex.org/W2068396114","https://openalex.org/W2071653495","https://openalex.org/W2072818362","https://openalex.org/W2084944189","https://openalex.org/W2100556411","https://openalex.org/W2101169619","https://openalex.org/W2110599581","https://openalex.org/W2117138194","https://openalex.org/W2120453412","https://openalex.org/W2121821935","https://openalex.org/W2122691893","https://openalex.org/W2129812935","https://openalex.org/W2134849720","https://openalex.org/W2139047213","https://openalex.org/W2143675408","https://openalex.org/W2145876682","https://openalex.org/W2146482778","https://openalex.org/W2149906003","https://openalex.org/W2150600350","https://openalex.org/W2160933580","https://openalex.org/W2162813111","https://openalex.org/W2163808566","https://openalex.org/W3097096317","https://openalex.org/W4237723258","https://openalex.org/W6632952189","https://openalex.org/W6633002085","https://openalex.org/W6635730845","https://openalex.org/W6676305975","https://openalex.org/W6677833576","https://openalex.org/W6680266532","https://openalex.org/W6681413097","https://openalex.org/W6681444772","https://openalex.org/W6682244693","https://openalex.org/W6683756719","https://openalex.org/W6684006261"],"related_works":["https://openalex.org/W1976822125","https://openalex.org/W2354159744","https://openalex.org/W4376123210","https://openalex.org/W2306105624","https://openalex.org/W2600867691","https://openalex.org/W2361270947","https://openalex.org/W2964008969","https://openalex.org/W2399434605","https://openalex.org/W2952357927","https://openalex.org/W2038416447"],"abstract_inverted_index":{"Classification":[0],"based":[1,19],"on":[2,137,188],"image":[3,18,32,36,46,112,133],"sets":[4,95,168],"has":[5],"recently":[6],"attracted":[7],"great":[8],"research":[9],"interest":[10],"as":[11,40,98,152,154],"it":[12],"holds":[13],"more":[14],"promise":[15],"than":[16,142],"single":[17,125],"classification.":[20,34],"In":[21],"this":[22,127,182],"paper,":[23],"we":[24],"propose":[25],"an":[26,51],"efficient":[27],"and":[28,50,146,171,192],"robust":[29],"algorithm":[30],"for":[31,63,131,161],"set":[33,37,134],"An":[35],"is":[38,59,96,169,177],"represented":[39],"a":[41,43,77,124],"triplet:":[42],"number":[44],"of":[45,69,72,93,114,123],"samples,":[47],"their":[48,102,115,155],"mean":[49],"affine":[52,56,70],"hull":[53,57],"model.":[54],"The":[55],"model":[58,144],"used":[60],"to":[61,179],"account":[62],"unseen":[64],"appearances":[65],"in":[66],"the":[67,91,99,111,132,138,143,149,163,172,189],"form":[68],"combinations":[71],"sample":[73,139],"images.":[74],"We":[75],"introduce":[76],"novel":[78,128],"between-set":[79],"distance":[80,100],"called":[81],"Sparse":[82],"Approximated":[83],"Nearest":[84],"Point":[85],"(SANP)":[86],"distance.":[87],"Unlike":[88],"existing":[89,197],"methods,":[90],"dissimilarity":[92],"two":[94,167],"measured":[97],"between":[101,166],"nearest":[103,150],"points,":[104],"which":[105],"can":[106],"be":[107],"sparsely":[108],"approximated":[109],"from":[110,119],"samples":[113],"respective":[116],"set.":[117],"Different":[118],"standard":[120],"sparse":[121,129,156],"modeling":[122],"image,":[126],"formulation":[130,160],"enforces":[135],"sparsity":[136],"coefficients":[140,145],"rather":[141],"jointly":[147],"optimizes":[148],"points":[151],"well":[153],"approximations.":[157],"A":[158],"convex":[159],"searching":[162],"optimal":[164],"SANP":[165],"proposed":[170],"accelerated":[173],"proximal":[174],"gradient":[175],"method":[176,202],"adapted":[178],"efficiently":[180],"solve":[181],"optimization.":[183],"Experimental":[184],"evaluation":[185],"was":[186],"performed":[187],"Honda,":[190],"MoBo":[191],"Youtube":[193],"datasets.":[194],"Comparison":[195],"with":[196],"techniques":[198],"shows":[199],"that":[200],"our":[201],"consistently":[203],"achieves":[204],"better":[205],"results.":[206]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":22},{"year":2017,"cited_by_count":37},{"year":2016,"cited_by_count":25},{"year":2015,"cited_by_count":36},{"year":2014,"cited_by_count":27},{"year":2013,"cited_by_count":19},{"year":2012,"cited_by_count":9}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}