{"id":"https://openalex.org/W2104807029","doi":"https://doi.org/10.1109/iccv.2009.5459439","title":"A multi-sample, multi-tree approach to bag-of-words image representation for image retrieval","display_name":"A multi-sample, multi-tree approach to bag-of-words image representation for image retrieval","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2104807029","doi":"https://doi.org/10.1109/iccv.2009.5459439","mag":"2104807029"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2009.5459439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459439","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/A5070394287","display_name":"Zhong Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Zhong Wu","raw_affiliation_strings":["Microsoft Research Limited, USA","Tsinghua University, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Limited, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111827722","display_name":"Qifa Ke","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Qifa Ke","raw_affiliation_strings":["Silicon Valley Laboratory, Microsoft Research"],"affiliations":[{"raw_affiliation_string":"Silicon Valley Laboratory, Microsoft Research","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004183775","display_name":"Jian Sun","orcid":"https://orcid.org/0000-0001-6530-9007"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Sun","raw_affiliation_strings":["Microsoft Research Asia"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111446552","display_name":"Heung-Yeung Shum","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heung-Yeung Shum","raw_affiliation_strings":["Microsoft Corporation, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070394287"],"corresponding_institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":4.2647,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.94736842,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1992","last_page":"1999"},"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":0.9987999796867371,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9941999912261963,"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/codebook","display_name":"Codebook","score":0.9117387533187866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7881607413291931},{"id":"https://openalex.org/keywords/visual-word","display_name":"Visual Word","score":0.7798788547515869},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7571114301681519},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.738115668296814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6980772018432617},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6505157947540283},{"id":"https://openalex.org/keywords/bag-of-words-model-in-computer-vision","display_name":"Bag-of-words model in computer vision","score":0.6197625994682312},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.5761796236038208},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5412970781326294},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.508503794670105},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.5080676078796387},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4966195225715637},{"id":"https://openalex.org/keywords/automatic-image-annotation","display_name":"Automatic image annotation","score":0.4749966859817505},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47009560465812683},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42099565267562866},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3413240909576416}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9117387533187866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7881607413291931},{"id":"https://openalex.org/C189391414","wikidata":"https://www.wikidata.org/wiki/Q7936579","display_name":"Visual Word","level":4,"score":0.7798788547515869},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7571114301681519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.738115668296814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6980772018432617},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6505157947540283},{"id":"https://openalex.org/C167611913","wikidata":"https://www.wikidata.org/wiki/Q6884747","display_name":"Bag-of-words model in computer vision","level":5,"score":0.6197625994682312},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.5761796236038208},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5412970781326294},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.508503794670105},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.5080676078796387},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4966195225715637},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.4749966859817505},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47009560465812683},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42099565267562866},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3413240909576416},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":3,"locations":[{"id":"doi:10.1109/iccv.2009.5459439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459439","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:10.1.1.164.1793","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.1793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/~jiansun/papers/MultiSampleTree_ICCV09.pdf","raw_type":"text"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-161308","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-161308","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W123402803","https://openalex.org/W1556531089","https://openalex.org/W1972418517","https://openalex.org/W1980911747","https://openalex.org/W2104170135","https://openalex.org/W2124404372","https://openalex.org/W2128017662","https://openalex.org/W2131846894","https://openalex.org/W2134446283","https://openalex.org/W2141362318","https://openalex.org/W2142194269","https://openalex.org/W2146776177","https://openalex.org/W2147237076","https://openalex.org/W2148809531","https://openalex.org/W2151103935","https://openalex.org/W2155979701","https://openalex.org/W2156598602","https://openalex.org/W2156854610","https://openalex.org/W2157941578","https://openalex.org/W2162808897","https://openalex.org/W2166118928","https://openalex.org/W2168133252","https://openalex.org/W2170146448","https://openalex.org/W2177274842","https://openalex.org/W2427881153","https://openalex.org/W6633472159","https://openalex.org/W6682431704","https://openalex.org/W6684614623"],"related_works":["https://openalex.org/W1615295117","https://openalex.org/W2158102958","https://openalex.org/W2035094092","https://openalex.org/W2277784908","https://openalex.org/W2045213079","https://openalex.org/W2938717424","https://openalex.org/W2587721114","https://openalex.org/W2032791227","https://openalex.org/W2179703327","https://openalex.org/W2518262377"],"abstract_inverted_index":{"The":[0],"state-of-the-art":[1],"content":[2],"based":[3],"image":[4,20,24,66,92,140],"retrieval":[5,67],"systems":[6],"has":[7],"been":[8],"significantly":[9],"advanced":[10],"by":[11,157],"the":[12,18,54,81,90,118,122,159],"introduction":[13],"of":[14,42,50,89,110,121],"SIFT":[15],"features":[16],"and":[17,37,53,113,135,152],"bag-of-words":[19],"representation.":[21],"Converting":[22],"an":[23],"into":[25],"a":[26,47,74,97,131,136,146],"bag-of-words,":[27],"however,":[28],"involves":[29],"three":[30],"non-trivial":[31],"steps:":[32],"feature":[33,35,38],"detection,":[34],"description,":[36],"quantization.":[39],"At":[40],"each":[41],"these":[43],"steps,":[44],"there":[45],"is":[46,105],"significant":[48,147],"amount":[49],"information":[51,88],"lost,":[52],"resulted":[55],"visual":[56,82,101,123],"words":[57],"are":[58],"often":[59],"not":[60],"discriminative":[61,100],"enough":[62],"for":[63],"large":[64,138],"scale":[65,139],"applications.":[68],"In":[69],"this":[70],"paper,":[71],"we":[72],"propose":[73],"novel":[75],"multi-sample":[76],"multi-tree":[77],"approach":[78,95,128],"to":[79],"computing":[80],"word":[83,102],"codebook.":[84],"By":[85],"encoding":[86],"more":[87,99],"original":[91,119],"feature,":[93],"our":[94,127,163],"generates":[96],"much":[98],"codebook":[103,160],"that":[104,145],"also":[106],"efficient":[107],"in":[108,149],"terms":[109],"both":[111,130,150],"computation":[112],"space":[114],"consumption,":[115],"without":[116],"losing":[117],"repeatability":[120],"features.":[124],"We":[125],"evaluate":[126],"using":[129,158],"ground-truth":[132],"data":[133],"set":[134],"real-world":[137],"database.":[141],"Our":[142],"results":[143],"show":[144],"improvement":[148],"precision":[151],"recall":[153],"can":[154],"be":[155],"achieved":[156],"derived":[161],"from":[162],"approach.":[164]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
