{"id":"https://openalex.org/W2607958226","doi":"https://doi.org/10.1109/icpr.2016.7900084","title":"Smart query expansion scheme for CDVS based on illumination and key features","display_name":"Smart query expansion scheme for CDVS based on illumination and key features","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2607958226","doi":"https://doi.org/10.1109/icpr.2016.7900084","mag":"2607958226"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900084","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900084","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5089404454","display_name":"Tao L\u00fc","orcid":"https://orcid.org/0000-0001-8117-2012"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Lu","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021302609","display_name":"Chuang Zhu","orcid":"https://orcid.org/0000-0001-5155-7069"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuang Zhu","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027946490","display_name":"Huizhu Jia","orcid":"https://orcid.org/0000-0002-2778-3768"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huizhu Jia","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024879728","display_name":"Ling\u2010Yu Duan","orcid":"https://orcid.org/0000-0002-4491-2023"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyu Duan","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455234","display_name":"Tao Li","orcid":"https://orcid.org/0000-0001-6399-1479"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Tao","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101565001","display_name":"Jiawen Song","orcid":"https://orcid.org/0000-0002-1818-7884"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiawen Song","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100536850","display_name":"Xiaodong Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Xie","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018478553","display_name":"Wen Gao","orcid":"https://orcid.org/0000-0002-8070-802X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Gao","raw_affiliation_strings":["Dept. EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Dept. EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5089404454"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20430567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2942","last_page":"2947"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9970999956130981,"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":0.996399998664856,"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/computer-science","display_name":"Computer science","score":0.8491783738136292},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.755805492401123},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5624011158943176},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5082201957702637},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4812714457511902},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.47964149713516235},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4702757000923157},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4663412272930145},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4566854238510132},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.45469915866851807},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4292583465576172},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.423922598361969},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38719579577445984},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38653549551963806},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3777986764907837}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8491783738136292},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.755805492401123},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5624011158943176},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5082201957702637},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4812714457511902},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.47964149713516235},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4702757000923157},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4663412272930145},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4566854238510132},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.45469915866851807},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4292583465576172},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.423922598361969},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38719579577445984},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38653549551963806},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3777986764907837},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7900084","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900084","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1510785568","https://openalex.org/W1970943680","https://openalex.org/W1976080191","https://openalex.org/W1979931042","https://openalex.org/W2023991840","https://openalex.org/W2067950595","https://openalex.org/W2076188996","https://openalex.org/W2100398441","https://openalex.org/W2135364649","https://openalex.org/W2141362318","https://openalex.org/W2151103935","https://openalex.org/W2186356322","https://openalex.org/W2537826750"],"related_works":["https://openalex.org/W2096359267","https://openalex.org/W2006459955","https://openalex.org/W2146885082","https://openalex.org/W2572349046","https://openalex.org/W4386051213","https://openalex.org/W185198413","https://openalex.org/W3125756434","https://openalex.org/W3049728138","https://openalex.org/W2348136644","https://openalex.org/W4239492988"],"abstract_inverted_index":{"Given":[0],"a":[1,11,94,112,140],"query":[2,80,95,122],"image,":[3],"retrieving":[4],"images":[5],"depicting":[6],"the":[7,32,79,88,134,148,152],"same":[8],"object":[9],"in":[10,91,120,164,170],"large":[12],"scale":[13],"database":[14],"is":[15,29,103],"becoming":[16],"an":[17,50,69],"urgent":[18],"and":[19,44,63,139,147,167],"challenging":[20],"task.":[21],"Recently,":[22],"Compact":[23],"Description":[24],"for":[25],"Visual":[26],"Search":[27],"(CDVS)":[28],"drafted":[30],"by":[31,87,160],"ISO/IEC":[33],"Moving":[34],"Pictures":[35],"Experts":[36],"Group":[37],"(MPEG)":[38],"to":[39,56,82,124],"support":[40],"image":[41],"retrieval":[42,126],"applications,":[43],"it":[45],"has":[46],"been":[47],"published":[48],"as":[49],"international":[51],"standard.":[52],"Unfortunately,":[53],"with":[54,58],"regard":[55],"applications":[57],"hugely":[59],"mutative":[60],"illumination,":[61],"perspective":[62],"noisy":[64],"background,":[65],"CDVS":[66],"suffers":[67],"from":[68],"inevitable":[70],"performance":[71,84],"loss.":[72],"In":[73],"this":[74],"paper,":[75],"firstly":[76],"we":[77,110],"introduce":[78],"expansion":[81,96,123],"address":[83],"loss":[85],"caused":[86],"scene":[89],"complexity":[90],"CDVS.":[92],"Secondly,":[93],"instance":[97],"selection":[98],"method":[99],"based":[100,117],"on":[101,133],"illumination":[102],"proposed,":[104],"which":[105],"achieves":[106],"better":[107],"performance.":[108,127],"Thirdly,":[109],"adopt":[111],"key":[113],"feature":[114],"matching":[115],"score":[116],"weighted":[118],"strategy":[119],"basic":[121],"improve":[125],"We":[128],"evaluate":[129],"our":[130],"proposed":[131,153],"methods":[132,154],"Oxford":[135,165],"(5K":[136],"images)":[137],"dataset":[138,144,166],"reality":[141],"traffic":[142],"vehicle":[143,171],"(12K":[145],"images),":[146],"result":[149],"shows":[150],"that":[151],"boost":[155],"mean":[156],"average":[157],"precision":[158],"(MAP)":[159],"7%":[161,168],"\u223c":[162],"10%":[163],"\u223c17%":[169],"dataset.":[172]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
