{"id":"https://openalex.org/W2168002178","doi":"https://doi.org/10.1109/cvpr.2005.320","title":"Shape Matching and Object Recognition Using Low Distortion Correspondences","display_name":"Shape Matching and Object Recognition Using Low Distortion Correspondences","publication_year":2005,"publication_date":"2005-07-27","ids":{"openalex":"https://openalex.org/W2168002178","doi":"https://doi.org/10.1109/cvpr.2005.320","mag":"2168002178"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2005.320","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2005.320","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5104361813","display_name":"Alexander C. Berg","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A.C. Berg","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of California Berkeley, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of California Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008309880","display_name":"Tamara L. Berg","orcid":"https://orcid.org/0000-0002-1272-3359"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T.L. Berg","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of California Berkeley, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of California Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001594573","display_name":"Jitendra Malik","orcid":"https://orcid.org/0000-0003-3695-1580"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Malik","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of California Berkeley, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of California Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":47.4486,"has_fulltext":false,"cited_by_count":853,"citation_normalized_percentile":{"value":0.99951182,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"1","issue":null,"first_page":"26","last_page":"33"},"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":0.9991999864578247,"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":0.9991999864578247,"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/T10057","display_name":"Face and Expression Recognition","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6866021752357483},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6526347398757935},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5207712054252625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4533705711364746},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4518822431564331},{"id":"https://openalex.org/keywords/spline","display_name":"Spline (mechanical)","score":0.4301924705505371},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4194610118865967},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4111732244491577},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37493622303009033},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3255237340927124}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6866021752357483},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6526347398757935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5207712054252625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4533705711364746},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4518822431564331},{"id":"https://openalex.org/C10390562","wikidata":"https://www.wikidata.org/wiki/Q581809","display_name":"Spline (mechanical)","level":2,"score":0.4301924705505371},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4194610118865967},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4111732244491577},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37493622303009033},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3255237340927124},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2005.320","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2005.320","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.72.8044","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.8044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.berkeley.edu/~aberg/papers/berg_correspondence.pdf","raw_type":"text"},{"id":"pmh:oai:berkeley.edu:13030-hb438nb4z3","is_oa":false,"landing_page_url":"http://techreports.lib.berkeley.edu/accessPages/CSD-04-1366.html","pdf_url":null,"source":{"id":"https://openalex.org/S7407050879","display_name":"UC Berkeley","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":"","raw_type":"technical reports"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W17011913","https://openalex.org/W1522847240","https://openalex.org/W1574225613","https://openalex.org/W1983024748","https://openalex.org/W2037090920","https://openalex.org/W2045798786","https://openalex.org/W2089181482","https://openalex.org/W2095757522","https://openalex.org/W2100983000","https://openalex.org/W2101522199","https://openalex.org/W2107558380","https://openalex.org/W2119823327","https://openalex.org/W2122903255","https://openalex.org/W2124087378","https://openalex.org/W2124386111","https://openalex.org/W2124465992","https://openalex.org/W2125791971","https://openalex.org/W2127597232","https://openalex.org/W2129116707","https://openalex.org/W2137154683","https://openalex.org/W2138742001","https://openalex.org/W2147474239","https://openalex.org/W2151103935","https://openalex.org/W2154422044","https://openalex.org/W2155511848","https://openalex.org/W2159709546","https://openalex.org/W2160754664","https://openalex.org/W2162708558","https://openalex.org/W2166049352","https://openalex.org/W2171188998","https://openalex.org/W2171490473","https://openalex.org/W2295106276","https://openalex.org/W3097096317","https://openalex.org/W3144510026","https://openalex.org/W3146079624","https://openalex.org/W3214102110","https://openalex.org/W6600679265","https://openalex.org/W6804270185"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1977636359","https://openalex.org/W2772305933","https://openalex.org/W2580722822"],"abstract_inverted_index":{"We":[0,126,165],"approach":[1,151],"recognition":[2,103],"in":[3,72,94,107],"the":[4,33,50,73,80,99,113,120,134],"framework":[5,111],"of":[6,41,55,67,75],"deformable":[7],"shape":[8],"matching,":[9],"relying":[10],"on":[11,39,129],"a":[12,88,95,108,153],"new":[13],"algorithm":[14,22,60],"for":[15,169],"finding":[16],"correspondences":[17],"between":[18,53,98,115,123],"feature":[19,57],"points.":[20,58,125],"This":[21],"sets":[23],"up":[24],"correspondence":[25,97],"as":[26,47,49],"an":[27,84,142],"integer":[28],"quadratic":[29],"programming":[30],"problem,":[31],"where":[32,112],"cost":[34,122],"function":[35],"has":[36],"terms":[37],"based":[38],"similarity":[40],"corresponding":[42,56,124],"geometric":[43,51],"blur":[44],"point":[45],"descriptors":[46],"well":[48],"distortion":[52],"pairs":[54],"The":[59],"handles":[61],"outliers,":[62],"and":[63,77,117,140,172],"thus":[64],"enables":[65],"matching":[66,121],"exemplars":[68],"to":[69,159,178,183],"query":[70,118],"images":[71],"presence":[74],"occlusion":[76],"clutter.":[78],"Given":[79],"correspondences,":[81],"we":[82],"estimate":[83],"aligning":[85],"transform,":[86],"typically":[87],"regularized":[89],"thin":[90],"plate":[91],"spline,":[92],"resulting":[93],"dense":[96],"two":[100,130],"shapes.":[101],"Object":[102],"is":[104,119,133],"then":[105],"handled":[106],"nearest":[109],"neighbor":[110],"distance":[114],"exemplar":[116],"show":[127,167],"results":[128,168],"datasets.":[131],"One":[132],"Caltech":[135],"101":[136],"dataset":[137,145],"(Fei-Fei,":[138],"Fergus":[139],"Perona),":[141],"extremely":[143],"challenging":[144],"with":[146],"large":[147],"intraclass":[148],"variation.":[149],"Our":[150],"yields":[152],"48%":[154],"correct":[155],"classification":[156],"rate,":[157],"compared":[158],"Fei-Fei":[160],"et":[161],"al":[162],"'s":[163],"16%.":[164],"also":[166],"localizing":[170],"frontal":[171],"profile":[173],"faces":[174],"that":[175],"are":[176],"comparable":[177],"special":[179],"purpose":[180],"approaches":[181],"tuned":[182],"faces.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":28},{"year":2019,"cited_by_count":32},{"year":2018,"cited_by_count":39},{"year":2017,"cited_by_count":28},{"year":2016,"cited_by_count":30},{"year":2015,"cited_by_count":72},{"year":2014,"cited_by_count":57},{"year":2013,"cited_by_count":64},{"year":2012,"cited_by_count":55}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
