{"id":"https://openalex.org/W2162248889","doi":"https://doi.org/10.1109/cvpr.2011.5995701","title":"Discriminative affine sparse codes for image classification","display_name":"Discriminative affine sparse codes for image classification","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2162248889","doi":"https://doi.org/10.1109/cvpr.2011.5995701","mag":"2162248889"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2011.5995701","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","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/A5021874113","display_name":"Naveen Kulkarni","orcid":"https://orcid.org/0000-0002-2644-7367"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Naveen Kulkarni","raw_affiliation_strings":["Computer Science and Engineering, Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032615847","display_name":"Baoxin Li","orcid":"https://orcid.org/0000-0002-9294-4572"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baoxin Li","raw_affiliation_strings":["Computer Science and Engineering, Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021874113"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":6.5397,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.97445466,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1609","last_page":"1616"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9926999807357788,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9926000237464905,"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":0.8739977478981018},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.819655179977417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7443804740905762},{"id":"https://openalex.org/keywords/affine-hull","display_name":"Affine hull","score":0.6995398998260498},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6931719779968262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.671798050403595},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5930657386779785},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.550502598285675},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5153002738952637},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.47237780690193176},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4649779796600342},{"id":"https://openalex.org/keywords/harris-affine-region-detector","display_name":"Harris affine region detector","score":0.4532358646392822},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4511871933937073},{"id":"https://openalex.org/keywords/affine-combination","display_name":"Affine combination","score":0.449752539396286},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4245995581150055},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3611246943473816},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3363913297653198},{"id":"https://openalex.org/keywords/affine-space","display_name":"Affine space","score":0.25279349088668823},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24572697281837463}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8739977478981018},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.819655179977417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7443804740905762},{"id":"https://openalex.org/C112128483","wikidata":"https://www.wikidata.org/wiki/Q382504","display_name":"Affine hull","level":4,"score":0.6995398998260498},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6931719779968262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.671798050403595},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5930657386779785},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.550502598285675},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5153002738952637},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.47237780690193176},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4649779796600342},{"id":"https://openalex.org/C6408098","wikidata":"https://www.wikidata.org/wiki/Q17021115","display_name":"Harris affine region detector","level":5,"score":0.4532358646392822},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4511871933937073},{"id":"https://openalex.org/C207221997","wikidata":"https://www.wikidata.org/wiki/Q938614","display_name":"Affine combination","level":3,"score":0.449752539396286},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4245995581150055},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3611246943473816},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3363913297653198},{"id":"https://openalex.org/C173110770","wikidata":"https://www.wikidata.org/wiki/Q382698","display_name":"Affine space","level":3,"score":0.25279349088668823},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24572697281837463},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2011.5995701","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1485562657","https://openalex.org/W1576445103","https://openalex.org/W1625255723","https://openalex.org/W1968969471","https://openalex.org/W1988790447","https://openalex.org/W1989975849","https://openalex.org/W2005876975","https://openalex.org/W2027922120","https://openalex.org/W2052094314","https://openalex.org/W2097018403","https://openalex.org/W2097360283","https://openalex.org/W2112447569","https://openalex.org/W2113606819","https://openalex.org/W2145073242","https://openalex.org/W2145406111","https://openalex.org/W2151103935","https://openalex.org/W2161946528","https://openalex.org/W2162881463","https://openalex.org/W2162915993","https://openalex.org/W2165828254","https://openalex.org/W2166742463","https://openalex.org/W4248437541","https://openalex.org/W4294541781","https://openalex.org/W6636494156","https://openalex.org/W6676727762","https://openalex.org/W6681651645"],"related_works":["https://openalex.org/W2184784635","https://openalex.org/W2038416447","https://openalex.org/W1510464305","https://openalex.org/W2077614002","https://openalex.org/W2347520500","https://openalex.org/W2106401644","https://openalex.org/W2783438186","https://openalex.org/W2361270947","https://openalex.org/W2393398535","https://openalex.org/W2079039086"],"abstract_inverted_index":{"Images":[0],"in":[1,38,45,55,151,191],"general":[2],"are":[3,70],"captured":[4,19],"under":[5],"a":[6,46,101,111,131],"diverse":[7],"set":[8],"of":[9,13,33,41,57,88,114,134],"conditions.":[10],"An":[11],"image":[12,34,105],"the":[14,42,58,165,170,179,184,192],"same":[15],"object":[16],"can":[17,51,182],"be":[18,52],"with":[20,90,174],"varied":[21,91],"poses,":[22],"illuminations,":[23],"scales,":[24],"backgrounds":[25],"and":[26,74,76,141],"probably":[27],"different":[28],"camera":[29,94],"parameters.":[30],"The":[31],"task":[32],"classification":[35],"then":[36,162],"lies":[37],"forming":[39],"features":[40,68,121,135],"input":[43,138],"images":[44,89],"representational":[47],"space":[48],"where":[49],"classifiers":[50],"better":[53],"supported":[54],"spite":[56],"above":[59],"variations.":[60],"Existing":[61],"methods":[62],"have":[63],"mostly":[64],"focused":[65],"on":[66,84],"obtaining":[67],"which":[69,86,107],"invariant":[71],"to":[72,153],"scale":[73],"translation,":[75],"thus":[77],"they":[78],"generally":[79],"suffer":[80],"from":[81,136],"performance":[82],"degradation":[83],"datasets":[85],"consist":[87],"poses":[92],"or":[93],"orientations.":[95],"In":[96],"this":[97,145],"paper":[98],"we":[99],"present":[100],"new":[102],"framework":[103],"for":[104],"classification,":[106],"is":[108,127,148,161],"built":[109],"upon":[110],"novel":[112,146],"way":[113],"feature":[115,147],"extraction":[116],"that":[117,144,178],"generates":[118],"largely":[119,155],"affine-invariant":[120],"called":[122],"affine":[123,166],"sparse":[124,167],"codes.":[125],"This":[126],"achieved":[128],"through":[129],"learning":[130],"compact":[132],"dictionary":[133],"affine-transformed":[137],"images.":[139],"Analysis":[140],"experiments":[142,173],"indicate":[143],"highly":[149],"discriminative":[150],"addition":[152],"being":[154],"affine-invariant.":[156],"A":[157],"classifier":[158],"using":[159,164],"AdaBoost":[160],"designed":[163],"codes":[168],"as":[169],"input.":[171],"Extensive":[172],"standard":[175],"databases":[176],"demonstrate":[177],"proposed":[180],"approach":[181],"obtain":[183],"state-of-the-art":[185],"results,":[186],"outperforming":[187],"existing":[188],"leading":[189],"approaches":[190],"literature.":[193]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":5}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}