{"id":"https://openalex.org/W1961095629","doi":"https://doi.org/10.1109/cvpr.2015.7299018","title":"Riemannian coding and dictionary learning: Kernels to the rescue","display_name":"Riemannian coding and dictionary learning: Kernels to the rescue","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1961095629","doi":"https://doi.org/10.1109/cvpr.2015.7299018","mag":"1961095629"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7299018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5021790939","display_name":"Mehrtash Harandi","orcid":"https://orcid.org/0000-0002-6937-6300"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Mehrtash Harandi","raw_affiliation_strings":["Australian National University & NICTA*, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Australian National University & NICTA*, Canberra, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049300388","display_name":"Mathieu Salzmann","orcid":"https://orcid.org/0000-0002-8347-8637"},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mathieu Salzmann","raw_affiliation_strings":["Australian National University & NICTA*, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Australian National University & NICTA*, Canberra, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I118347636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021790939"],"corresponding_institution_ids":["https://openalex.org/I118347636","https://openalex.org/I42894916"],"apc_list":null,"apc_paid":null,"fwci":19.0974,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.99703759,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3926","last_page":"3935"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9955000281333923,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9955000281333923,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9955000281333923,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.994700014591217,"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/generality","display_name":"Generality","score":0.7786960005760193},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5633915662765503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5533581972122192},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5199783444404602},{"id":"https://openalex.org/keywords/riemannian-geometry","display_name":"Riemannian geometry","score":0.509797990322113},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.5091909766197205},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.47546905279159546},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4725232720375061},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.45187777280807495},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39948558807373047},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3890123963356018},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3421841859817505},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34136074781417847},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.20664647221565247},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.09541529417037964},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0902208685874939}],"concepts":[{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.7786960005760193},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5633915662765503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5533581972122192},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5199783444404602},{"id":"https://openalex.org/C181104567","wikidata":"https://www.wikidata.org/wiki/Q761383","display_name":"Riemannian geometry","level":2,"score":0.509797990322113},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.5091909766197205},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.47546905279159546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4725232720375061},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.45187777280807495},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39948558807373047},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3890123963356018},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3421841859817505},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34136074781417847},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.20664647221565247},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.09541529417037964},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0902208685874939},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2015.7299018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.710.5602","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.710.5602","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://www.nicta.com.au/content/uploads/2015/05/HarandiSalzmannCVPR15.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W3219084","https://openalex.org/W1479760883","https://openalex.org/W1508406818","https://openalex.org/W1540155273","https://openalex.org/W1549083695","https://openalex.org/W1578054159","https://openalex.org/W1808256548","https://openalex.org/W1963932623","https://openalex.org/W1964321627","https://openalex.org/W1966385142","https://openalex.org/W1969763012","https://openalex.org/W1984309565","https://openalex.org/W1991183060","https://openalex.org/W1995707608","https://openalex.org/W2004465977","https://openalex.org/W2027922120","https://openalex.org/W2047643928","https://openalex.org/W2048192550","https://openalex.org/W2062811091","https://openalex.org/W2068935349","https://openalex.org/W2069170077","https://openalex.org/W2090042335","https://openalex.org/W2091804476","https://openalex.org/W2096484739","https://openalex.org/W2097018403","https://openalex.org/W2099095260","https://openalex.org/W2099129729","https://openalex.org/W2104978738","https://openalex.org/W2112447569","https://openalex.org/W2122319321","https://openalex.org/W2123745357","https://openalex.org/W2123921160","https://openalex.org/W2125389556","https://openalex.org/W2126017757","https://openalex.org/W2128638419","https://openalex.org/W2129812935","https://openalex.org/W2132467081","https://openalex.org/W2134563198","https://openalex.org/W2142040002","https://openalex.org/W2144093206","https://openalex.org/W2144273546","https://openalex.org/W2145889472","https://openalex.org/W2146932984","https://openalex.org/W2147942061","https://openalex.org/W2149652297","https://openalex.org/W2153786187","https://openalex.org/W2155490028","https://openalex.org/W2155541015","https://openalex.org/W2162915993","https://openalex.org/W2163737036","https://openalex.org/W2166049352","https://openalex.org/W2166118928","https://openalex.org/W2167164761","https://openalex.org/W2169678505","https://openalex.org/W2184852195","https://openalex.org/W2228536296","https://openalex.org/W2242953327","https://openalex.org/W2953139536","https://openalex.org/W2984925782"],"related_works":["https://openalex.org/W2793063187","https://openalex.org/W2161305109","https://openalex.org/W3012953444","https://openalex.org/W2511045973","https://openalex.org/W2081533887","https://openalex.org/W22502857","https://openalex.org/W2895515333","https://openalex.org/W3010037765","https://openalex.org/W204290405","https://openalex.org/W2157785665"],"abstract_inverted_index":{"While":[0],"sparse":[1,80],"coding":[2,49,64,88,110],"on":[3,22,53,119],"non-flat":[4,124],"Riemannian":[5,54,63,109,139],"manifolds":[6],"has":[7],"recently":[8],"become":[9],"increasingly":[10],"popular,":[11],"existing":[12],"solutions":[13,85],"either":[14],"are":[15,26,138],"dedicated":[16],"to":[17,28,34,42,47,86,133],"specific":[18],"manifolds,":[19,125],"or":[20],"rely":[21],"optimization":[23],"problems":[24],"that":[25],"difficult":[27],"solve,":[29],"especially":[30],"when":[31],"it":[32,132],"comes":[33],"dictionary":[35,51,100],"learning.":[36],"In":[37],"this":[38,57],"paper,":[39],"we":[40,59],"propose":[41],"make":[43],"use":[44],"of":[45,79,116,123],"kernels":[46],"perform":[48,96],"and":[50,98,126],"learning":[52,101],"manifolds.":[55,140],"To":[56],"end,":[58],"introduce":[60,83],"a":[61,103],"general":[62],"framework":[65],"with":[66],"its":[67,128],"kernel-based":[68],"counterpart.":[69],"This":[70],"lets":[71],"us":[72],"(i)":[73],"generalize":[74],"beyond":[75],"the":[76,92,114],"special":[77],"case":[78],"coding;":[81],"(ii)":[82],"efficient":[84],"two":[87],"schemes;":[89],"(iii)":[90],"learn":[91],"kernel":[93],"parameters;":[94],"(iv)":[95],"unsupervised":[97],"supervised":[99],"in":[102],"much":[104],"simpler":[105],"manner":[106],"than":[107],"previous":[108],"methods.":[111],"We":[112],"demonstrate":[113],"effectiveness":[115],"our":[117],"approach":[118],"three":[120],"different":[121],"types":[122],"illustrate":[127],"generality":[129],"by":[130],"applying":[131],"Euclidean":[134],"spaces,":[135],"which":[136],"also":[137]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":14},{"year":2016,"cited_by_count":24},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}