{"id":"https://openalex.org/W2168753605","doi":"https://doi.org/10.1109/tcsvt.2011.2129150","title":"Learning to Extract Focused Objects From Low DOF Images","display_name":"Learning to Extract Focused Objects From Low DOF Images","publication_year":2011,"publication_date":"2011-03-17","ids":{"openalex":"https://openalex.org/W2168753605","doi":"https://doi.org/10.1109/tcsvt.2011.2129150","mag":"2168753605"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2011.2129150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2011.2129150","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-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/A5114378292","display_name":"Hongliang Li","orcid":"https://orcid.org/0000-0002-7481-095X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongliang Li","raw_affiliation_strings":["School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062332580","display_name":"King Ngi Ngan","orcid":"https://orcid.org/0000-0003-1946-3235"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"King N. Ngan","raw_affiliation_strings":["Department of Electronic Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5114378292"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":9.0768,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.97983372,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"21","issue":"11","first_page":"1571","last_page":"1580"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9948999881744385,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9779999852180481,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8585928678512573},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6990216970443726},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6610829830169678},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6354206204414368},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6005869507789612},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5777771472930908},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5460801124572754},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5286073088645935},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48860055208206177},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4854643940925598},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.43472588062286377},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4326574206352234},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4187106192111969},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.41727426648139954},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25050002336502075}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8585928678512573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6990216970443726},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6610829830169678},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6354206204414368},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6005869507789612},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5777771472930908},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5460801124572754},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5286073088645935},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48860055208206177},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4854643940925598},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.43472588062286377},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4326574206352234},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4187106192111969},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.41727426648139954},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25050002336502075}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2011.2129150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2011.2129150","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W10619482","https://openalex.org/W10828093","https://openalex.org/W1968058417","https://openalex.org/W1999478155","https://openalex.org/W2011811856","https://openalex.org/W2106524364","https://openalex.org/W2108082645","https://openalex.org/W2112301665","https://openalex.org/W2121947440","https://openalex.org/W2122893959","https://openalex.org/W2124351162","https://openalex.org/W2126322579","https://openalex.org/W2128272608","https://openalex.org/W2129004009","https://openalex.org/W2138221429","https://openalex.org/W2140274257","https://openalex.org/W2141303268","https://openalex.org/W2149035855","https://openalex.org/W2149310070","https://openalex.org/W2150464846","https://openalex.org/W2155871590","https://openalex.org/W2164598857","https://openalex.org/W2166655058","https://openalex.org/W2167499379","https://openalex.org/W2169041475","https://openalex.org/W2169551590","https://openalex.org/W2170146448","https://openalex.org/W2535516436","https://openalex.org/W2536208356","https://openalex.org/W4248635988","https://openalex.org/W6600410602","https://openalex.org/W6678695112","https://openalex.org/W6681769576"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W4231274751","https://openalex.org/W2963610131","https://openalex.org/W4387272257","https://openalex.org/W2134401318","https://openalex.org/W1555506570","https://openalex.org/W1966354130","https://openalex.org/W4200301313"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3],"approach":[4],"to":[5,87,116],"extract":[6],"focused":[7,19],"objects":[8],"(i.e.,":[9],"attention":[10],"objects)":[11],"from":[12,42],"low":[13],"depth-of-field":[14],"images.":[15],"To":[16],"recognize":[17],"the":[18,23,61,71,89,118,135,139],"object,":[20],"we":[21,111],"decompose":[22],"image":[24],"into":[25],"multiple":[26],"regions,":[27],"which":[28],"are":[29],"described":[30],"by":[31,70,120],"using":[32,106],"three":[33],"types":[34],"of":[35,45,48,64,73,94,132,138],"visual":[36,75],"descriptors.":[37],"Each":[38],"descriptor":[39],"is":[40],"extracted":[41,74],"a":[43,52,65,79,84,92,98,113,130],"representation":[44],"some":[46],"aspects":[47],"local":[49],"appearance,":[50],"e.g.,":[51],"spatially":[53],"localized":[54],"texture,":[55],"color,":[56],"or":[57],"geometrical":[58],"property.":[59],"Therefore,":[60],"focus":[62],"detection":[63],"region":[66,122],"can":[67,103],"be":[68,104],"achieved":[69,105],"classification":[72,108],"descriptors":[76],"based":[77],"on":[78,129],"binary":[80],"classifier.":[81],"We":[82],"employ":[83],"boosting":[85],"algorithm":[86],"learn":[88],"classifier":[90],"with":[91,144],"cascade":[93],"decision":[95],"structure.":[96],"Given":[97],"test":[99],"image,":[100],"initial":[101],"segmentation":[102],"obtained":[107],"results.":[109],"Finally,":[110],"apply":[112],"post-processing":[114],"technique":[115],"improve":[117],"results":[119],"incorporating":[121],"grouping":[123],"and":[124],"pixel-level":[125],"segmentation.":[126],"Experimental":[127],"evaluation":[128],"number":[131],"images":[133],"demonstrates":[134],"performance":[136],"advantages":[137],"proposed":[140],"method,":[141],"when":[142],"compared":[143],"state-of-the-art":[145],"methods.":[146]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
