{"id":"https://openalex.org/W2532478580","doi":"https://doi.org/10.1109/iccv.2009.5459178","title":"Beyond the Euclidean distance: Creating effective visual codebooks using the Histogram Intersection Kernel","display_name":"Beyond the Euclidean distance: Creating effective visual codebooks using the Histogram Intersection Kernel","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2532478580","doi":"https://doi.org/10.1109/iccv.2009.5459178","mag":"2532478580"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2009.5459178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","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/A5090881698","display_name":"Jianxin Wu","orcid":"https://orcid.org/0000-0002-2085-7568"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jianxin Wu","raw_affiliation_strings":["Center for Robotics and Intelligent Machines, School of Interactive Computing, Georgia Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Center for Robotics and Intelligent Machines, School of Interactive Computing, Georgia Institute of Technology, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002228469","display_name":"James M. Rehg","orcid":"https://orcid.org/0000-0003-1793-5462"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James M Rehg","raw_affiliation_strings":["Center for Robotics and Intelligent Machines, School of Interactive Computing, Georgia Institute of Technology, USA"],"affiliations":[{"raw_affiliation_string":"Center for Robotics and Intelligent Machines, School of Interactive Computing, Georgia Institute of Technology, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5090881698"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":23.6199,"has_fulltext":false,"cited_by_count":244,"citation_normalized_percentile":{"value":0.9963416,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"630","last_page":"637"},"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":1.0,"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":1.0,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9990000128746033,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.9059991836547852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7388269901275635},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6629539728164673},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6236340999603271},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5515803098678589},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5447472333908081},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.528035044670105},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.4995455741882324},{"id":"https://openalex.org/keywords/histogram-matching","display_name":"Histogram matching","score":0.4245741367340088},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.41674262285232544},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40019410848617554},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.32208752632141113},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22434690594673157},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.11812147498130798}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9059991836547852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7388269901275635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6629539728164673},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6236340999603271},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5515803098678589},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5447472333908081},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.528035044670105},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.4995455741882324},{"id":"https://openalex.org/C127449775","wikidata":"https://www.wikidata.org/wiki/Q3785871","display_name":"Histogram matching","level":4,"score":0.4245741367340088},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.41674262285232544},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40019410848617554},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.32208752632141113},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22434690594673157},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.11812147498130798},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv.2009.5459178","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459178","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.150.324","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cc.gatech.edu/~wujx/paper/iccv_2009.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1565746575","https://openalex.org/W2053941121","https://openalex.org/W2073459066","https://openalex.org/W2113855951","https://openalex.org/W2120738995","https://openalex.org/W2121627225","https://openalex.org/W2122808326","https://openalex.org/W2125574651","https://openalex.org/W2126338813","https://openalex.org/W2128017662","https://openalex.org/W2131846894","https://openalex.org/W2132870739","https://openalex.org/W2134380836","https://openalex.org/W2140095548","https://openalex.org/W2141303268","https://openalex.org/W2145406111","https://openalex.org/W2146022472","https://openalex.org/W2147625498","https://openalex.org/W2148596671","https://openalex.org/W2148809531","https://openalex.org/W2151103935","https://openalex.org/W2151259137","https://openalex.org/W2153635508","https://openalex.org/W2155231285","https://openalex.org/W2155904486","https://openalex.org/W2157941578","https://openalex.org/W2159184562","https://openalex.org/W2160978182","https://openalex.org/W2161969291","https://openalex.org/W2162915993","https://openalex.org/W2164996087","https://openalex.org/W2166742463","https://openalex.org/W2186094539","https://openalex.org/W2293597654","https://openalex.org/W2914885528","https://openalex.org/W3120421331","https://openalex.org/W6677051642","https://openalex.org/W6683233156","https://openalex.org/W6686583229","https://openalex.org/W6697214482"],"related_works":["https://openalex.org/W2158102958","https://openalex.org/W2028757524","https://openalex.org/W1995462736","https://openalex.org/W2938717424","https://openalex.org/W2548286644","https://openalex.org/W2009049007","https://openalex.org/W2588241640","https://openalex.org/W2045213079","https://openalex.org/W2465112410","https://openalex.org/W2616303661"],"abstract_inverted_index":{"Common":[0],"visual":[1,27,33,85,131,173],"codebook":[2,108,174],"generation":[3,83,175],"methods":[4],"used":[5,74,171],"in":[6,57,75],"a":[7,89,123,180],"Bag":[8],"of":[9,37,84],"Visual":[10],"words":[11,133],"model,":[12],"e.g.":[13],"k-means":[14,92,115,185],"or":[15],"Gaussian":[16],"Mixture":[17],"Model,":[18],"use":[19],"the":[20,45,54,82,164],"Euclidean":[21,55],"distance":[22,56],"to":[23,79,97,127],"cluster":[24],"features":[25],"into":[26],"code":[28,132],"words.":[29],"However,":[30],"most":[31],"popular":[32,151],"descriptors":[34],"are":[35],"histograms":[36],"image":[38],"measurements.":[39],"It":[40],"has":[41,109,143],"been":[42],"shown":[43],"that":[44,69,163],"Histogram":[46],"Intersection":[47],"Kernel":[48],"(HIK)":[49],"is":[50,95],"more":[51,129],"effective":[52,130],"than":[53],"supervised":[58],"learning":[59],"tasks":[60],"with":[61],"histogram":[62,90],"features.":[63],"In":[64,119,159],"this":[65],"paper,":[66],"we":[67,121,161],"demonstrate":[68],"HIK":[70,107,183],"can":[71,135,169,177],"also":[72],"be":[73,170],"an":[76],"unsupervised":[77],"manner":[78],"significantly":[80],"improve":[81],"codebooks.":[86],"We":[87],"propose":[88,122],"kernel":[91],"algorithm":[93],"which":[94,134],"easy":[96],"implement":[98],"and":[99,156,176,184],"runs":[100],"almost":[101],"as":[102,104,179],"fast":[103],"k-means.":[105],"The":[106,140],"consistently":[110],"higher":[111,138],"recognition":[112],"accuracy":[113],"over":[114],"codebooks":[116],"by":[117],"2-4%.":[118],"addition,":[120,160],"one-class":[124],"SVM":[125],"formulation":[126],"create":[128],"achieve":[136],"even":[137],"accuracy.":[139],"proposed":[141],"method":[142,168],"established":[144],"new":[145],"state-of-the-art":[146],"performance":[147],"numbers":[148],"for":[149,172],"3":[150],"benchmark":[152],"datasets":[153],"on":[154],"object":[155],"scene":[157],"recognition.":[158],"show":[162],"standard":[165],"k-median":[166],"clustering":[167],"act":[178],"compromise":[181],"between":[182],"approaches.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":22},{"year":2015,"cited_by_count":30},{"year":2014,"cited_by_count":41},{"year":2013,"cited_by_count":33},{"year":2012,"cited_by_count":28}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}