{"id":"https://openalex.org/W2753723525","doi":"https://doi.org/10.1109/icip.2017.8296342","title":"Weighted median-shift on graphs for geometric model fitting","display_name":"Weighted median-shift on graphs for geometric model fitting","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2753723525","doi":"https://doi.org/10.1109/icip.2017.8296342","mag":"2753723525"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5040981898","display_name":"Xiong Zhou","orcid":"https://orcid.org/0000-0002-0897-7508"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiong Zhou","raw_affiliation_strings":["Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044594971","display_name":"Hanzi Wang","orcid":"https://orcid.org/0000-0002-6913-9786"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanzi Wang","raw_affiliation_strings":["Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050524397","display_name":"Guobao Xiao","orcid":"https://orcid.org/0000-0003-2928-8100"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guobao Xiao","raw_affiliation_strings":["Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100754894","display_name":"Xing Wang","orcid":"https://orcid.org/0000-0002-7176-7036"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Wang","raw_affiliation_strings":["Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395059","display_name":"Yan Yan","orcid":"https://orcid.org/0000-0002-3674-7160"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yan","raw_affiliation_strings":["Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China"],"affiliations":[{"raw_affiliation_string":"Pujian Key Laboratory of Sensing and Computing for Smart City, Xiamen University, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100646618","display_name":"Liming Zhang","orcid":"https://orcid.org/0000-0002-2664-8193"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Liming Zhang","raw_affiliation_strings":["Faculty of Science and Technology, University of Macau, Macau, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5040981898"],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":0.182,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56973122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"555","last_page":"559"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection 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/T12549","display_name":"Image and Object Detection 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9972000122070312,"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/weighting","display_name":"Weighting","score":0.73341304063797},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6939327120780945},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.551387369632721},{"id":"https://openalex.org/keywords/mean-shift","display_name":"Mean-shift","score":0.4934138357639313},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4930374324321747},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4537622332572937},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4483564496040344},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4479658901691437},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4409297704696655},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43610087037086487},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4352647364139557},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38104185461997986},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.33973586559295654},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1795644462108612}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.73341304063797},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6939327120780945},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.551387369632721},{"id":"https://openalex.org/C48548287","wikidata":"https://www.wikidata.org/wiki/Q6803557","display_name":"Mean-shift","level":3,"score":0.4934138357639313},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4930374324321747},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4537622332572937},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4483564496040344},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4479658901691437},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4409297704696655},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43610087037086487},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4352647364139557},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38104185461997986},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.33973586559295654},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1795644462108612},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296342","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W331959685","https://openalex.org/W1519594923","https://openalex.org/W1558894666","https://openalex.org/W2009953720","https://openalex.org/W2026375818","https://openalex.org/W2053627315","https://openalex.org/W2071975644","https://openalex.org/W2082712442","https://openalex.org/W2085261163","https://openalex.org/W2097338724","https://openalex.org/W2110116386","https://openalex.org/W2114430732","https://openalex.org/W2114674762","https://openalex.org/W2116925220","https://openalex.org/W2135245997","https://openalex.org/W2137145201","https://openalex.org/W2148093566","https://openalex.org/W2154201540","https://openalex.org/W2162246463","https://openalex.org/W2171728525","https://openalex.org/W2202222344","https://openalex.org/W2205514457","https://openalex.org/W2395024868","https://openalex.org/W2538325766","https://openalex.org/W6679914928","https://openalex.org/W6680439912","https://openalex.org/W6683304699","https://openalex.org/W6728384960"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2023748438","https://openalex.org/W2124385053","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W2108418243","https://openalex.org/W164103134","https://openalex.org/W2169903804","https://openalex.org/W2787352659"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,67,84,102],"deal":[4,126],"with":[5,127,130],"geometric":[6],"model":[7,17,27,123,155],"fitting":[8,156],"problems":[9],"on":[10,63,73,138],"graphs,":[11],"where":[12],"each":[13,20,90],"vertex":[14,91],"represents":[15,22],"a":[16,55,69,86,131],"hypothesis,":[18],"and":[19,35,79,125,142],"edge":[21],"the":[23,40,47,61,94,97,106,120,146,149],"similarity":[24],"between":[25],"two":[26],"hypotheses.":[28],"Conventional":[29],"median-shift":[30,72],"methods":[31],"are":[32],"very":[33],"efficient":[34],"they":[36,45],"can":[37,58,117],"automatically":[38],"estimate":[39,119],"number":[41,121,133],"of":[42,54,96,122,134,148],"clusters.":[43],"However,":[44],"assign":[46,85],"same":[48],"weighting":[49,87],"scores":[50],"to":[51,77,89,93,111],"all":[52],"vertices":[53,104,109],"graph,":[56],"which":[57],"not":[59],"show":[60,145],"discriminability":[62],"different":[64],"vertices.":[65],"Therefore,":[66],"propose":[68],"novel":[70],"weighted":[71,107],"graphs":[74],"method":[75,116,151],"(WMSG)":[76],"fit":[78],"segment":[80],"multiple-structure":[81],"data.":[82],"Specifically,":[83],"score":[88],"according":[92],"distribution":[95],"corresponding":[98],"inliers.":[99],"After":[100],"that,":[101],"shift":[103],"towards":[105],"median":[108],"iteratively":[110],"detect":[112],"modes.":[113],"The":[114],"proposed":[115,150],"adaptively":[118],"instances":[124],"data":[128,141],"contaminated":[129],"large":[132],"outliers.":[135],"Experimental":[136],"results":[137],"both":[139],"synthetic":[140],"real":[143],"images":[144],"advantages":[147],"over":[152],"several":[153],"state-of-the-art":[154],"methods.":[157]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}