{"id":"https://openalex.org/W2135974317","doi":"https://doi.org/10.1109/cvpr.2008.4587636","title":"Fast kernel learning for spatial pyramid matching","display_name":"Fast kernel learning for spatial pyramid matching","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2135974317","doi":"https://doi.org/10.1109/cvpr.2008.4587636","mag":"2135974317"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","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/A5101252047","display_name":"Junfeng He","orcid":"https://orcid.org/0009-0004-5465-5659"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junfeng He","raw_affiliation_strings":["Department of Electrical Engineering, Columbia University, New York, NY, USA","Dept. of Electr. Eng., Columbia Univ., New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Columbia Univ., New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037340457","display_name":"Shih\u2010Fu Chang","orcid":"https://orcid.org/0000-0003-1444-1205"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shih-Fu Chang","raw_affiliation_strings":["Department of Electrical Engineering, Columbia University, New York, NY, USA","Dept. of Electr. Eng., Columbia Univ., New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Columbia Univ., New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049449495","display_name":"Lexing Xie","orcid":"https://orcid.org/0000-0001-8319-0118"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lexing Xie","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","Dept. of Electrical Engineering, Columbia Univ., New York, 10027, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Hawthorne, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Columbia Univ., New York, 10027, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0854,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.89182252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9904000163078308,"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/kernel","display_name":"Kernel (algebra)","score":0.7769722938537598},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.649492621421814},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.629402756690979},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5942491292953491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5887184739112854},{"id":"https://openalex.org/keywords/quadratic-programming","display_name":"Quadratic programming","score":0.5453152656555176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5373529195785522},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5288673043251038},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.508531928062439},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5054209232330322},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.49566900730133057},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.4814697802066803},{"id":"https://openalex.org/keywords/semidefinite-programming","display_name":"Semidefinite programming","score":0.4645395576953888},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37686699628829956},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33090728521347046},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.26747822761535645},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2520444691181183},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.14199015498161316},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07753169536590576}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7769722938537598},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.649492621421814},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.629402756690979},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5942491292953491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5887184739112854},{"id":"https://openalex.org/C81845259","wikidata":"https://www.wikidata.org/wiki/Q290117","display_name":"Quadratic programming","level":2,"score":0.5453152656555176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5373529195785522},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5288673043251038},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.508531928062439},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5054209232330322},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.49566900730133057},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.4814697802066803},{"id":"https://openalex.org/C101901036","wikidata":"https://www.wikidata.org/wiki/Q2269096","display_name":"Semidefinite programming","level":2,"score":0.4645395576953888},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37686699628829956},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33090728521347046},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26747822761535645},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2520444691181183},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.14199015498161316},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07753169536590576},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cvpr.2008.4587636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587636","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.153.4421","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.4421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ee.columbia.edu/dvmm/publications/08/FKLforSPM_cvpr08.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.324.2764","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.324.2764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/Conference/data/papers/296.pdf","raw_type":"text"},{"id":"pmh:oai:openresearch-repository.anu.edu.au:1885/57858","is_oa":false,"landing_page_url":"http://hdl.handle.net/1885/57858","pdf_url":null,"source":{"id":"https://openalex.org/S4306402539","display_name":"ANU Open Research (Australian National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I118347636","host_organization_name":"Australian National University","host_organization_lineage":["https://openalex.org/I118347636"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of CVPR 2008","raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1589362500","https://openalex.org/W1967879792","https://openalex.org/W1984707692","https://openalex.org/W2031823405","https://openalex.org/W2092483655","https://openalex.org/W2104978738","https://openalex.org/W2105225065","https://openalex.org/W2105464770","https://openalex.org/W2107034620","https://openalex.org/W2118670840","https://openalex.org/W2124386111","https://openalex.org/W2129156852","https://openalex.org/W2131846894","https://openalex.org/W2139823104","https://openalex.org/W2142387771","https://openalex.org/W2145295623","https://openalex.org/W2154683974","https://openalex.org/W2159727956","https://openalex.org/W2162915993","https://openalex.org/W2166049352","https://openalex.org/W6635107798","https://openalex.org/W6641446668","https://openalex.org/W6646428394","https://openalex.org/W6677669521","https://openalex.org/W6680434193"],"related_works":["https://openalex.org/W2352839224","https://openalex.org/W2371590971","https://openalex.org/W2203098598","https://openalex.org/W1653317167","https://openalex.org/W1989828432","https://openalex.org/W2187390889","https://openalex.org/W2135796990","https://openalex.org/W2024017812","https://openalex.org/W2725311638","https://openalex.org/W2123146423"],"abstract_inverted_index":{"Spatial":[0],"pyramid":[1],"matching":[2],"(SPM)":[3],"is":[4,63],"a":[5,34],"simple":[6],"yet":[7],"effective":[8],"approach":[9,38,62],"to":[10,39,73],"compute":[11],"similarity":[12],"between":[13],"images.":[14],"Similarity":[15],"kernels":[16],"at":[17],"different":[18],"regions":[19],"and":[20,36,111],"scales":[21],"are":[22],"usually":[23],"fused":[24],"by":[25,42,100],"some":[26],"heuristic":[27],"weights.":[28],"In":[29],"this":[30],"paper,":[31],"we":[32],"develop":[33],"novel":[35,65],"fast":[37],"improve":[40],"SPM":[41],"finding":[43],"the":[44,64,97],"optimal":[45],"kernel":[46,68],"fusing":[47],"weights":[48],"from":[49],"multiple":[50],"scales,":[51],"locations,":[52],"as":[53,55,108],"well":[54],"codebooks.":[56],"One":[57],"unique":[58],"contribution":[59],"of":[60,67,96],"our":[61],"formulation":[66],"matrix":[69],"learning":[70],"problem":[71],"leading":[72],"an":[74],"efficient":[75],"quadratic":[76],"programming":[77],"solution,":[78],"with":[79,86],"much":[80],"lower":[81],"complexity":[82],"than":[83],"those":[84],"associated":[85],"existing":[87],"solutions":[88],"(e.g.,":[89],"semidefinite":[90],"programming).":[91],"We":[92],"demonstrate":[93],"performance":[94],"gains":[95],"proposed":[98],"methods":[99],"evaluations":[101],"over":[102],"well-known":[103],"public":[104],"data":[105],"sets":[106],"such":[107],"natural":[109],"scenes":[110],"TRECVID":[112],"2007.":[113]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
