{"id":"https://openalex.org/W2003754073","doi":"https://doi.org/10.1109/icip.2010.5651309","title":"How context helps: A discriminative codeword selection method for object detection","display_name":"How context helps: A discriminative codeword selection method for object detection","publication_year":2010,"publication_date":"2010-09-01","ids":{"openalex":"https://openalex.org/W2003754073","doi":"https://doi.org/10.1109/icip.2010.5651309","mag":"2003754073"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2010.5651309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5651309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Image Processing","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/A5052852448","display_name":"Renzhong Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Renzhong Wei","raw_affiliation_strings":["Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070355771","display_name":"Hong Lu","orcid":"https://orcid.org/0000-0002-4572-2854"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Lu","raw_affiliation_strings":["Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056833841","display_name":"Yingbin Zheng","orcid":"https://orcid.org/0000-0002-5590-9292"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingbin Zheng","raw_affiliation_strings":["Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085349440","display_name":"Lei Cen","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Cen","raw_affiliation_strings":["Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625873","display_name":"Cheng Jin","orcid":"https://orcid.org/0000-0003-3063-1957"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Jin","raw_affiliation_strings":["Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003418019","display_name":"Xiangyang Xue","orcid":"https://orcid.org/0000-0002-4897-9209"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyang Xue","raw_affiliation_strings":["Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intel. Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Shanghai Key Lab of Intel. Infor. Processing, School of Computer Science, Fudan University, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029236990","display_name":"Weiguo Wu","orcid":"https://orcid.org/0000-0002-1179-3435"},"institutions":[{"id":"https://openalex.org/I4210110621","display_name":"Sony (China)","ror":"https://ror.org/02qd2bv04","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210110621","https://openalex.org/I4210143797"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiguo Wu","raw_affiliation_strings":["Sony China Research Laboratory, Beijing, China","Sony China Research Laboratory Beijing, China"],"affiliations":[{"raw_affiliation_string":"Sony China Research Laboratory, Beijing, China","institution_ids":["https://openalex.org/I4210110621"]},{"raw_affiliation_string":"Sony China Research Laboratory Beijing, China","institution_ids":["https://openalex.org/I4210110621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5052852448"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":1.5936,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.83959293,"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":"3905","last_page":"3908"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.996999979019165,"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":0.9890000224113464,"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/discriminative-model","display_name":"Discriminative model","score":0.9158376455307007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.843372642993927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7358237504959106},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6999889612197876},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.673482358455658},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.6540642380714417},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5654869079589844},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5266551971435547},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5220898985862732},{"id":"https://openalex.org/keywords/viola\u2013jones-object-detection-framework","display_name":"Viola\u2013Jones object detection framework","score":0.46795761585235596},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.4164070188999176},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.41144245862960815},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3944574296474457},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.14314323663711548}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9158376455307007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.843372642993927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7358237504959106},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6999889612197876},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.673482358455658},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.6540642380714417},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5654869079589844},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5266551971435547},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5220898985862732},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.46795761585235596},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.4164070188999176},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.41144245862960815},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3944574296474457},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.14314323663711548},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2010.5651309","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2010.5651309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1625255723","https://openalex.org/W2062903088","https://openalex.org/W2066690519","https://openalex.org/W2107034620","https://openalex.org/W2112020727","https://openalex.org/W2120369594","https://openalex.org/W2128272608","https://openalex.org/W2131846894","https://openalex.org/W2151103935","https://openalex.org/W2162915993","https://openalex.org/W2164996087","https://openalex.org/W2168583292","https://openalex.org/W2172188317","https://openalex.org/W2186094539","https://openalex.org/W6636494156","https://openalex.org/W7075742223"],"related_works":["https://openalex.org/W3034955165","https://openalex.org/W2094920358","https://openalex.org/W2041448692","https://openalex.org/W2247121321","https://openalex.org/W2391926582","https://openalex.org/W2087391438","https://openalex.org/W1966831329","https://openalex.org/W2316074893","https://openalex.org/W957444674","https://openalex.org/W3160205797"],"abstract_inverted_index":{"We":[0],"first":[1],"propose":[2,111,199],"in":[3,9,88,120,125,138,154],"this":[4,139,168],"paper":[5],"to":[6,54,60,65,92,112,132,173,200],"localize":[7],"objects":[8,81],"images":[10,90],"based":[11,47],"on":[12,48,209],"the":[13,17,41,56,62,67,76,79,84,89,98,114,121,126,134,148,151,155,177,183,187,222,225],"models":[14],"learned":[15],"from":[16,44,78,100,176,182],"weakly":[18],"labeled":[19],"images.":[20],"This":[21,157],"task":[22,130,158,169],"is":[23,69,102,131,159,172],"termed":[24,160],"as":[25,34,161],"region":[26],"of":[27,150,224],"interest":[28],"(ROI)":[29],"detection.":[30,163,206],"Local":[31],"features":[32,175],"such":[33],"SIFT":[35,49],"or":[36],"HOG":[37,51],"are":[38,52],"extracted":[39,190],"and":[40,50,108,123,145,180,214],"discriminative":[42,63,115,188,196],"words":[43,64,85,116,189,203],"clustered":[45],"codewords":[46],"selected":[53],"model":[55,66],"objects.":[57],"Then":[58],"how":[59],"find":[61],"object":[68,106,152,205],"important.":[70],"Existing":[71],"ROI":[72,171,192],"detection":[73,107,193],"methods":[74],"consider":[75],"information":[77,99],"foreground":[80],"by":[82],"selecting":[83],"appearing":[86,153],"more":[87,119],"belonging":[91],"one":[93],"specific":[94],"image":[95,144],"class.":[96],"Considering":[97],"background/context":[101],"also":[103,146],"helpful":[104],"for":[105,141,167,204],"classification,":[109],"we":[110,198],"select":[113],"which":[117],"appear":[118],"foreground/object":[122],"less":[124],"background/context.":[127],"Second,":[128],"another":[129],"give":[133,147],"class":[135],"label":[136],"(object":[137],"setting)":[140],"a":[142,215],"given":[143],"position":[149],"image.":[156,185],"objection":[162],"A":[164],"normal":[165],"way":[166],"after":[170],"extract":[174],"detected":[178],"regions":[179],"not":[181],"whole":[184],"Since":[186],"during":[191],"has":[194],"good":[195],"ability,":[197],"use":[201],"these":[202],"Experimental":[207],"results":[208],"PASCAL":[210],"VOC":[211],"2006":[212],"dataset":[213,217],"larger":[216],"containing":[218],"29":[219],"classes":[220],"demonstrate":[221],"effectiveness":[223],"proposed":[226],"method.":[227]},"counts_by_year":[{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}