{"id":"https://openalex.org/W2098381762","doi":"https://doi.org/10.1109/iccv.2003.1238349","title":"Minimum risk distance measure for object recognition","display_name":"Minimum risk distance measure for object recognition","publication_year":2003,"publication_date":"2003-01-01","ids":{"openalex":"https://openalex.org/W2098381762","doi":"https://doi.org/10.1109/iccv.2003.1238349","mag":"2098381762"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2003.1238349","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2003.1238349","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings Ninth IEEE International Conference on Computer Vision","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Minimum_Risk_Distance_Measure_for_Object_Recognition/6555548","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070883186","display_name":"Mahamud","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mahamud","raw_affiliation_strings":["Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","Dept. of Comput. Sci., Carnegie-Mellon Univ., Pittsburgh, PA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Carnegie-Mellon Univ., Pittsburgh, PA, USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025339565","display_name":"Hebert","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hebert","raw_affiliation_strings":["Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","Dept. of Comput. Sci., Carnegie-Mellon Univ., Pittsburgh, PA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Carnegie-Mellon Univ., Pittsburgh, PA, USA#TAB#","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5070883186"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.961,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.9155066,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"242","last_page":"248 vol.1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9973000288009644,"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/T10057","display_name":"Face and Expression Recognition","score":0.9973000288009644,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.7892457246780396},{"id":"https://openalex.org/keywords/statistical-distance","display_name":"Statistical distance","score":0.7240474820137024},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.685951292514801},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5105980038642883},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.509323239326477},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.500187873840332},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48630985617637634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48541077971458435},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48539555072784424},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.46062272787094116},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17650309205055237},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16054630279541016},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.14965283870697021}],"concepts":[{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.7892457246780396},{"id":"https://openalex.org/C58948655","wikidata":"https://www.wikidata.org/wiki/Q7604392","display_name":"Statistical distance","level":3,"score":0.7240474820137024},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.685951292514801},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5105980038642883},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.509323239326477},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.500187873840332},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48630985617637634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48541077971458435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48539555072784424},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.46062272787094116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17650309205055237},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16054630279541016},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.14965283870697021},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1109/iccv.2003.1238349","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2003.1238349","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings Ninth IEEE International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.cmu.edu:robotics-1447","is_oa":false,"landing_page_url":"http://repository.cmu.edu/robotics/448","pdf_url":null,"source":{"id":"https://openalex.org/S4306400668","display_name":"Research Showcase @ Carnegie Mellon University (Carnegie Mellon University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I74973139","host_organization_name":"Carnegie Mellon University","host_organization_lineage":["https://openalex.org/I74973139"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Robotics Institute","raw_type":"text"},{"id":"pmh:doi:10.1184/r1/6555548","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal contribution"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.331.9013","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.331.9013","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://lear.inrialpes.fr/people/triggs/events/iccv03/cdrom/iccv03/0242_mahamud.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.7.6308","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.7.6308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cmu.edu/~mahamud/iccv-2003.pdf","raw_type":"text"},{"id":"pmh:oai:figshare.com:article/6555548","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Minimum_Risk_Distance_Measure_for_Object_Recognition/6555548","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.1184/r1/6555548.v1","is_oa":true,"landing_page_url":"https://doi.org/10.1184/r1/6555548.v1","pdf_url":null,"source":{"id":"https://openalex.org/S7407050927","display_name":"KiltHub Repository","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/6555548","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Minimum_Risk_Distance_Measure_for_Object_Recognition/6555548","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6399999856948853,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1493297678","https://openalex.org/W1667165204","https://openalex.org/W2033419168","https://openalex.org/W2036488048","https://openalex.org/W2053666650","https://openalex.org/W2088779313","https://openalex.org/W2091696547","https://openalex.org/W2103971661","https://openalex.org/W2112359824","https://openalex.org/W2118774738","https://openalex.org/W2121647436","https://openalex.org/W2122111042","https://openalex.org/W2124925761","https://openalex.org/W2138451337","https://openalex.org/W2140758332","https://openalex.org/W2143784448","https://openalex.org/W2156909104","https://openalex.org/W2170120409","https://openalex.org/W2799061466","https://openalex.org/W2942228371","https://openalex.org/W4230674625","https://openalex.org/W4230946174","https://openalex.org/W6675924963","https://openalex.org/W6676645178"],"related_works":["https://openalex.org/W2098381762","https://openalex.org/W1540729820","https://openalex.org/W2043253481","https://openalex.org/W2080446023","https://openalex.org/W2393169369","https://openalex.org/W2137617983","https://openalex.org/W2492030843","https://openalex.org/W4389338221","https://openalex.org/W2157426608","https://openalex.org/W194843333"],"abstract_inverted_index":{"The":[0],"optimal":[1,41,90],"distance":[2,42,50,76,91,100,103,123],"measure":[3,43,77,92],"for":[4,66],"a":[5,22,134,149],"given":[6],"discrimination":[7,152],"task":[8,153],"under":[9,132],"the":[10,19,40,74,85,89,98,106,121,128,162,165],"nearest":[11],"neighbor":[12],"framework":[13],"has":[14],"been":[15],"shown":[16],"to":[17,87,113],"be":[18],"likelihood":[20],"that":[21,62,109,156],"pair":[23],"of":[24,164],"measurements":[25],"have":[26,105],"different":[27],"class":[28],"labels":[29],"[S.":[30],"Mahamud":[31],"et":[32],"al.,":[33],"(2002)].":[34],"For":[35],"implementation":[36],"and":[37,154],"efficiency":[38],"considerations,":[39],"was":[44],"approximated":[45],"by":[46],"combining":[47],"more":[48],"elementary":[49,75,99,122],"measures":[51,104,124],"defined":[52],"on":[53,148],"simple":[54,94],"feature":[55,80,95],"spaces.":[56],"We":[57,83,126,140],"address":[58],"two":[59],"important":[60],"issues":[61],"arise":[63],"in":[64,78,93],"practice":[65],"such":[67,102],"an":[68],"approach:":[69],"(a)":[70],"What":[71],"form":[72],"should":[73],"each":[79],"space":[81],"take?":[82],"motivate":[84],"need":[86],"use":[88],"spaces":[96],"as":[97],"measures;":[101],"desirable":[107],"property":[108],"they":[110],"are":[111],"invariant":[112],"distance-respecting":[114],"transformations,":[115],"(b)":[116],"How":[117],"do":[118],"we":[119],"combine":[120],"?":[125],"present":[127],"precise":[129],"statistical":[130],"assumptions":[131],"which":[133],"linear":[135],"logistic":[136],"model":[137,143],"holds":[138],"exactly.":[139],"benchmark":[141],"our":[142,157],"with":[144,161],"three":[145],"other":[146],"methods":[147],"challenging":[150],"face":[151],"show":[155],"approach":[158],"is":[159],"competitive":[160],"state":[163],"art.":[166]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}