{"id":"https://openalex.org/W1998596683","doi":"https://doi.org/10.1109/cvpr.2008.4587435","title":"Generalised blurring mean-shift algorithms for nonparametric clustering","display_name":"Generalised blurring mean-shift algorithms for nonparametric clustering","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W1998596683","doi":"https://doi.org/10.1109/cvpr.2008.4587435","mag":"1998596683"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","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/A5057957982","display_name":"Miguel \u00c1. Carreira-Perpi\u00f1\u00e1n","orcid":"https://orcid.org/0000-0003-3297-9375"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Miguel A. Carreira-Perpinan","raw_affiliation_strings":["EECS, School of Engineering, University of California, Merced, USA","Sch. of Eng., California Univ., Merced, CA"],"affiliations":[{"raw_affiliation_string":"EECS, School of Engineering, University of California, Merced, USA","institution_ids":["https://openalex.org/I156087764"]},{"raw_affiliation_string":"Sch. of Eng., California Univ., Merced, CA","institution_ids":["https://openalex.org/I156087764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5057957982"],"corresponding_institution_ids":["https://openalex.org/I156087764"],"apc_list":null,"apc_paid":null,"fwci":1.8721,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.84717546,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9952999949455261,"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":0.9952999949455261,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9750000238418579,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9735000133514404,"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/mean-shift","display_name":"Mean-shift","score":0.7106602787971497},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.696772575378418},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6191733479499817},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.5620511770248413},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5598722100257874},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5196589231491089},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.5040461421012878},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.49577412009239197},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.45277056097984314},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4102644920349121},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.2585853636264801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2220938503742218},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.09029459953308105},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08758920431137085}],"concepts":[{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.7106602787971497},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.696772575378418},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6191733479499817},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.5620511770248413},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5598722100257874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5196589231491089},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.5040461421012878},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.49577412009239197},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.45277056097984314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4102644920349121},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2585853636264801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2220938503742218},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.09029459953308105},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08758920431137085},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2008.4587435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1996376324","https://openalex.org/W2000214666","https://openalex.org/W2022686119","https://openalex.org/W2067191022","https://openalex.org/W2074886232","https://openalex.org/W2079017595","https://openalex.org/W2107413231","https://openalex.org/W2121947440","https://openalex.org/W2136277000","https://openalex.org/W2141240481","https://openalex.org/W2164500538","https://openalex.org/W2294984095","https://openalex.org/W6676270023","https://openalex.org/W6697018953"],"related_works":["https://openalex.org/W90906771","https://openalex.org/W2018828772","https://openalex.org/W2529185025","https://openalex.org/W2945629716","https://openalex.org/W4283775266","https://openalex.org/W3043533097","https://openalex.org/W4298860769","https://openalex.org/W2767126220","https://openalex.org/W2159429390","https://openalex.org/W3007770227"],"abstract_inverted_index":{"Gaussian":[0,86],"blurring":[1],"mean-shift":[2,32],"(GBMS)":[3],"is":[4],"a":[5,10,31,37,63,117],"nonparametric":[6],"clustering":[7,114],"algorithm,":[8],"having":[9],"single":[11],"bandwidth":[12,169],"parameter":[13],"that":[14,81,107],"controls":[15],"the":[16,24,28,70,74,82,100,108,130,139,155,161,168],"number":[17],"of":[18,30,48,76,167],"clusters.":[19],"The":[20],"algorithm":[21],"iteratively":[22],"shrinks":[23],"data":[25],"set":[26],"under":[27],"application":[29],"update,":[33],"stops":[34],"in":[35,138,145,176,185],"just":[36],"few":[38],"iterations":[39],"and":[40,57,60,79,94,102,123,128,148,170],"yields":[41],"excellent":[42],"clusterings.":[43],"We":[44,66,105],"propose":[45],"several":[46],"families":[47],"generalised":[49],"GBMS":[50],"(GGBMS)":[51],"algorithms":[52,78,109,157],"based":[53],"on":[54,62,69,99],"explicit,":[55],"implicit":[56],"exponential":[58],"updates,":[59],"depending":[61,98],"step-size":[64],"parameter.":[65],"give":[67],"conditions":[68],"step":[71,103,171],"size":[72],"for":[73,85,135],"convergence":[75,83],"these":[77],"show":[80,106,129,151],"rate":[84],"clusters":[87],"ranges":[88],"from":[89],"sublinear":[90],"to":[91,112],"linear,":[92],"cubic":[93],"even":[95],"higher":[96],"order":[97],"update":[101],"size.":[104],"are":[110],"related":[111],"spectral":[113],"if":[115],"using":[116],"random-walk":[118],"matrix":[119],"with":[120,132,178],"modified":[121],"eigenvalues":[122],"updated":[124],"after":[125],"each":[126],"iteration,":[127],"relation":[131],"methods":[133],"developed":[134],"surface":[136],"smoothing":[137],"computer":[140],"graphics":[141],"literature.":[142],"Detailed":[143],"experiments":[144],"toy":[146],"problems":[147],"image":[149],"segmentation":[150],"that,":[152],"while":[153],"all":[154],"GGBMS":[156],"can":[158],"achieve":[159],"essentially":[160],"same":[162],"result":[163],"(for":[164],"appropriate":[165],"settings":[166],"size),":[172],"they":[173],"significantly":[174],"differ":[175],"runtime,":[177],"slightly":[179],"over-relaxed":[180],"explicit":[181],"updates":[182],"being":[183],"fastest":[184],"practice.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}