{"id":"https://openalex.org/W3120293235","doi":"https://doi.org/10.1109/ijcb48548.2020.9304932","title":"All-in-Focus Iris Camera With a Great Capture Volume","display_name":"All-in-Focus Iris Camera With a Great Capture Volume","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3120293235","doi":"https://doi.org/10.1109/ijcb48548.2020.9304932","mag":"3120293235"},"language":"en","primary_location":{"id":"doi:10.1109/ijcb48548.2020.9304932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb48548.2020.9304932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Joint Conference on Biometrics (IJCB)","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/A5079579315","display_name":"Kunbo Zhang","orcid":"https://orcid.org/0000-0002-4826-6831"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kunbo Zhang","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, National Lab of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, National Lab of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051408218","display_name":"Zhenteng Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160996","display_name":"Tianjin Academy for Intelligent Recognition Technologies","ror":"https://ror.org/05wd2ky28","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210160996"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenteng Shen","raw_affiliation_strings":["Tianjin Academy for Intelligent Recognition Technologies, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Academy for Intelligent Recognition Technologies, Tianjin, China","institution_ids":["https://openalex.org/I4210160996"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100398969","display_name":"Yunlong Wang","orcid":"https://orcid.org/0000-0002-3535-308X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunlong Wang","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, National Lab of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, National Lab of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055505703","display_name":"Zhenan Sun","orcid":"https://orcid.org/0000-0003-4029-9935"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenan Sun","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, National Lab of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, National Lab of Pattern Recognition, Institute of Automation Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079579315"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"],"apc_list":null,"apc_paid":null,"fwci":0.7546,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79534523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9968000054359436,"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":0.9968000054359436,"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":0.9866999983787537,"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/T10828","display_name":"Biometric Identification and Security","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/focus","display_name":"Focus (optics)","score":0.7759841680526733},{"id":"https://openalex.org/keywords/iris","display_name":"IRIS (biosensor)","score":0.7480788826942444},{"id":"https://openalex.org/keywords/iris-recognition","display_name":"Iris recognition","score":0.7065005898475647},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6956696510314941},{"id":"https://openalex.org/keywords/depth-of-field","display_name":"Depth of field","score":0.6904453635215759},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6879367828369141},{"id":"https://openalex.org/keywords/lens","display_name":"Lens (geology)","score":0.665189266204834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6122947335243225},{"id":"https://openalex.org/keywords/cardinal-point","display_name":"Cardinal point","score":0.5975046753883362},{"id":"https://openalex.org/keywords/autofocus","display_name":"Autofocus","score":0.5792467594146729},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5390498042106628},{"id":"https://openalex.org/keywords/focal-length","display_name":"Focal length","score":0.47138768434524536},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.4706422686576843},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.45192641019821167},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13835397362709045}],"concepts":[{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.7759841680526733},{"id":"https://openalex.org/C2779503344","wikidata":"https://www.wikidata.org/wiki/Q5973514","display_name":"IRIS (biosensor)","level":3,"score":0.7480788826942444},{"id":"https://openalex.org/C112356035","wikidata":"https://www.wikidata.org/wiki/Q1672722","display_name":"Iris recognition","level":3,"score":0.7065005898475647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6956696510314941},{"id":"https://openalex.org/C183072630","wikidata":"https://www.wikidata.org/wiki/Q215932","display_name":"Depth of field","level":2,"score":0.6904453635215759},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6879367828369141},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.665189266204834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6122947335243225},{"id":"https://openalex.org/C138395690","wikidata":"https://www.wikidata.org/wiki/Q376733","display_name":"Cardinal point","level":2,"score":0.5975046753883362},{"id":"https://openalex.org/C103764139","wikidata":"https://www.wikidata.org/wiki/Q210008","display_name":"Autofocus","level":3,"score":0.5792467594146729},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5390498042106628},{"id":"https://openalex.org/C82552819","wikidata":"https://www.wikidata.org/wiki/Q193540","display_name":"Focal length","level":3,"score":0.47138768434524536},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.4706422686576843},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.45192641019821167},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13835397362709045},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb48548.2020.9304932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb48548.2020.9304932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G7625510445","display_name":null,"funder_award_id":"2017YFB0801900","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1629771433","https://openalex.org/W1773296250","https://openalex.org/W1964090263","https://openalex.org/W1975786763","https://openalex.org/W1980612221","https://openalex.org/W2001874327","https://openalex.org/W2008533014","https://openalex.org/W2036494508","https://openalex.org/W2042418988","https://openalex.org/W2073815107","https://openalex.org/W2088714418","https://openalex.org/W2092988036","https://openalex.org/W2097346583","https://openalex.org/W2116361875","https://openalex.org/W2134453323","https://openalex.org/W2297633669","https://openalex.org/W2460425166","https://openalex.org/W2472683490","https://openalex.org/W2730947821","https://openalex.org/W2794775595","https://openalex.org/W2885260968","https://openalex.org/W2949929875","https://openalex.org/W4231616929","https://openalex.org/W6637898176","https://openalex.org/W6641149958","https://openalex.org/W6644300382","https://openalex.org/W6645277275"],"related_works":["https://openalex.org/W1968827811","https://openalex.org/W2079188893","https://openalex.org/W3206931886","https://openalex.org/W4320061889","https://openalex.org/W1515588876","https://openalex.org/W1787360621","https://openalex.org/W2106467180","https://openalex.org/W2026494525","https://openalex.org/W3187266571","https://openalex.org/W3215565456"],"abstract_inverted_index":{"Imaging":[0],"volume":[1,67],"of":[2,76,114,128,137,151,171],"an":[3,117],"iris":[4,32,51,73,123,162,173],"recognition":[5,33,174],"system":[6,53,79,158],"has":[7],"been":[8],"restricting":[9],"the":[10,26,89,98,104,109,126,149,169],"throughput":[11],"and":[12,39,58,84,111,168],"cooperation":[13],"convenience":[14],"in":[15,30,116,159],"biometric":[16],"applications.":[17],"Numerous":[18],"improvement":[19],"trials":[20],"are":[21],"still":[22],"impractical":[23],"to":[24,35,63,87,107,131],"supersede":[25],"dominant":[27],"fixed-focus":[28],"lens":[29,57],"stand-off":[31],"due":[34],"incremental":[36],"performance":[37],"increase":[38],"complicated":[40],"optical":[41],"design.":[42],"In":[43,96],"this":[44,152],"study,":[45],"we":[46],"develop":[47],"a":[48,55,59],"novel":[49],"all-in-focus":[50,122],"imaging":[52,74,157],"using":[54,164],"focus-tunable":[56],"2D":[60],"steering":[61,156],"mirror":[62,101],"greatly":[64],"extend":[65,108],"capture":[66],"by":[68],"spatiotemporal":[69],"multiplexing":[70],"method.":[71],"Our":[72],"depth":[75,127],"field":[77,113,129],"extension":[78],"requires":[80],"no":[81],"mechanical":[82],"motion":[83],"is":[85,135],"capable":[86],"adjust":[88],"focal":[90,143,166],"plane":[91],"at":[92],"extremely":[93],"high":[94],"speed.":[95],"addition,":[97],"motorized":[99],"reflection":[100],"adaptively":[102],"steers":[103],"light":[105,154],"beam":[106,155],"horizontal":[110],"vertical":[112],"views":[115],"active":[118],"manner.":[119],"The":[120],"proposed":[121],"camera":[124],"increases":[125],"up":[130],"3.9":[132],"m":[133],"which":[134],"afactor":[136],"37.5":[138],"compared":[139],"with":[140],"conventional":[141],"long":[142],"lens.":[144],"We":[145],"also":[146],"experimentally":[147],"demonstrate":[148],"capability":[150],"3D":[153],"real-time":[160],"multi-person":[161],"refocusing":[163],"dynamic":[165],"stacks":[167],"potential":[170],"continuous":[172],"for":[175],"moving":[176],"participants.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}