{"id":"https://openalex.org/W1956061132","doi":"https://doi.org/10.5220/0004661802990304","title":"Large-scale Image Retrieval based on the Vocabulary Tree","display_name":"Large-scale Image Retrieval based on the Vocabulary Tree","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W1956061132","doi":"https://doi.org/10.5220/0004661802990304","mag":"1956061132"},"language":"en","primary_location":{"id":"doi:10.5220/0004661802990304","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004661802990304","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0004661802990304","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100640942","display_name":"Bo Cheng","orcid":"https://orcid.org/0000-0003-2160-2839"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Cheng","raw_affiliation_strings":["Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448036","display_name":"Zhuo Li","orcid":"https://orcid.org/0000-0002-9937-2669"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhuo","raw_affiliation_strings":["Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100415699","display_name":"Pei Zhang","orcid":"https://orcid.org/0000-0003-1423-7992"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pei Zhang","raw_affiliation_strings":["Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052709846","display_name":"Jing Zhang","orcid":"https://orcid.org/0000-0003-3516-0111"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Zhang","raw_affiliation_strings":["Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Signal & Information Processing Laboratory Beijing University of Technology, China#TAB#","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100640942"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.2439,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54847292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"299","last_page":"304"},"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":0.9995999932289124,"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":0.9995999932289124,"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":0.9983000159263611,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9466999769210815,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.7764662504196167},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.7043821811676025},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6099312901496887},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5917794704437256},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.5629631280899048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5444579720497131},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5276828408241272},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5244926810264587},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4292116165161133},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11471560597419739},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.09590259194374084},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08608242869377136},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08526891469955444}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7764662504196167},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.7043821811676025},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6099312901496887},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5917794704437256},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.5629631280899048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5444579720497131},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5276828408241272},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5244926810264587},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4292116165161133},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11471560597419739},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.09590259194374084},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08608242869377136},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08526891469955444},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0004661802990304","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004661802990304","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0004661802990304","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004661802990304","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6800000071525574,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W2053437444","https://openalex.org/W2119605622","https://openalex.org/W2124222502","https://openalex.org/W2128017662","https://openalex.org/W2145072179","https://openalex.org/W2151103935","https://openalex.org/W2152322845","https://openalex.org/W2163652601","https://openalex.org/W2177274842"],"related_works":["https://openalex.org/W2349784553","https://openalex.org/W3022596247","https://openalex.org/W2601444686","https://openalex.org/W4292238148","https://openalex.org/W2137671468","https://openalex.org/W4323660495","https://openalex.org/W1979153711","https://openalex.org/W2385319785","https://openalex.org/W766546768","https://openalex.org/W1991655505"],"abstract_inverted_index":{"In":[0],"this":[1,22],"paper,":[2],"vocabulary":[3,109],"tree":[4],"based":[5],"large-scale":[6,116],"image":[7,76,117,124],"retrieval":[8,134],"scheme":[9],"is":[10,52,71,84],"proposed":[11,129],"that":[12],"can":[13,24,131],"achieve":[14,132],"higher":[15],"accuracy":[16],"and":[17,92],"speed.":[18],"The":[19,119],"novelty":[20],"of":[21,44,49,90],"paper":[23],"be":[25,74,113],"summarized":[26],"as":[27],"follows.":[28],"First,":[29],"because":[30],"traditional":[31],"Scale":[32],"Invariant":[33],"Feature":[34],"Transform":[35],"(SIFT)":[36],"descriptors":[37],"are":[38,105],"excessively":[39],"concentrated":[40],"in":[41,64],"some":[42],"areas":[43],"images,":[45],"the":[46,56,88,128],"extraction":[47],"process":[48],"SIFT":[50,91],"features":[51,104],"optimized":[53],"to":[54,73,86,98,107],"reduce":[55,87],"number.":[57],"Then,":[58],"combined":[59],"with":[60],"optimized-SIFT,":[61],"color":[62,69,93],"histogram":[63],"Hue,":[65],"Saturation,":[66],"Value":[67],"(HSV)":[68],"space":[70],"extracted":[72],"another":[75],"feature.":[77],"Moreover,":[78],"Local":[79],"Fisher":[80],"Discriminant":[81],"Analysis":[82],"(LFDA)":[83],"applied":[85],"dimension":[89],"features,":[94],"which":[95,111],"will":[96,112],"help":[97],"shorten":[99],"feature-clustering":[100],"time.":[101],"Finally,":[102],"dimension-reduced":[103],"used":[106,114],"generate":[108],"trees":[110],"for":[115],"retrieval.":[118],"experimental":[120],"results":[121],"on":[122],"several":[123],"datasets":[125],"show":[126],"that,":[127],"method":[130],"satisfying":[133],"precision.":[135]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}