{"id":"https://openalex.org/W3115482011","doi":"https://doi.org/10.1109/iccma51325.2020.9301545","title":"More Informed Random Sample Consensus","display_name":"More Informed Random Sample Consensus","publication_year":2020,"publication_date":"2020-11-06","ids":{"openalex":"https://openalex.org/W3115482011","doi":"https://doi.org/10.1109/iccma51325.2020.9301545","mag":"3115482011"},"language":"en","primary_location":{"id":"doi:10.1109/iccma51325.2020.9301545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccma51325.2020.9301545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 8th International Conference on Control, Mechatronics and Automation (ICCMA)","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/A5102980184","display_name":"Guoxiang Zhang","orcid":"https://orcid.org/0000-0002-4531-2628"},"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":false,"raw_author_name":"Guoxiang Zhang","raw_affiliation_strings":["School of Engineering, UC Merced, Merced, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, UC Merced, Merced, USA","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100715957","display_name":"YangQuan Chen","orcid":"https://orcid.org/0000-0002-7422-5988"},"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":false,"raw_author_name":"YangQuan Chen","raw_affiliation_strings":["School of Engineering, UC Merced, Merced, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, UC Merced, Merced, USA","institution_ids":["https://openalex.org/I156087764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I156087764"],"apc_list":null,"apc_paid":null,"fwci":8.1605,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.97319572,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"197","last_page":"201"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9987999796867371,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9983999729156494,"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/ransac","display_name":"RANSAC","score":0.9387691020965576},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.6630412936210632},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6582787036895752},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6463775634765625},{"id":"https://openalex.org/keywords/image-stitching","display_name":"Image stitching","score":0.6435463428497314},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5532936453819275},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5174999237060547},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4867822825908661},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4345843195915222},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43201425671577454},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4259111285209656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4136892557144165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3637996315956116},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2811563313007355},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2265230417251587}],"concepts":[{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.9387691020965576},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.6630412936210632},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6582787036895752},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6463775634765625},{"id":"https://openalex.org/C29081049","wikidata":"https://www.wikidata.org/wiki/Q1364242","display_name":"Image stitching","level":2,"score":0.6435463428497314},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5532936453819275},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5174999237060547},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4867822825908661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4345843195915222},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43201425671577454},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4259111285209656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4136892557144165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3637996315956116},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2811563313007355},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2265230417251587},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccma51325.2020.9301545","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccma51325.2020.9301545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 8th International Conference on Control, Mechatronics and Automation (ICCMA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1957167950","https://openalex.org/W1974014252","https://openalex.org/W2012319351","https://openalex.org/W2024548552","https://openalex.org/W2026375818","https://openalex.org/W2046434485","https://openalex.org/W2085261163","https://openalex.org/W2106199912","https://openalex.org/W2114759747","https://openalex.org/W2130017587","https://openalex.org/W2130871783","https://openalex.org/W2347795126","https://openalex.org/W2545834714","https://openalex.org/W2556455135","https://openalex.org/W2782122348","https://openalex.org/W2796442735","https://openalex.org/W2890752431","https://openalex.org/W2962828767","https://openalex.org/W3139835851","https://openalex.org/W4229995443","https://openalex.org/W6729099241","https://openalex.org/W6747722499"],"related_works":["https://openalex.org/W1565457536","https://openalex.org/W2353412837","https://openalex.org/W2981534051","https://openalex.org/W3202772837","https://openalex.org/W2373863823","https://openalex.org/W1974289846","https://openalex.org/W4200038363","https://openalex.org/W2379442087","https://openalex.org/W2953367949","https://openalex.org/W3171899115"],"abstract_inverted_index":{"Random":[0],"sample":[1],"consensus":[2],"(RANSAC)":[3],"is":[4,10,25,76,114],"a":[5,51,57,62,79,92],"robust":[6],"model-fitting":[7],"algorithm.":[8,65],"It":[9],"widely":[11],"used":[12],"in":[13,96],"many":[14,44],"fields":[15],"including":[16],"image-stitching":[17],"and":[18,119],"point":[19,94],"cloud":[20],"registration.":[21],"In":[22,46,66],"RANSAC,":[23],"data":[24,55,63,75,86,93,107],"uniformly":[26],"sampled":[27,103],"for":[28],"hypothesis":[29,68],"generation.":[30],"However,":[31],"this":[32,47],"uniform":[33,131],"sampling":[34,69],"strategy":[35],"does":[36],"not":[37],"fully":[38],"utilize":[39],"all":[40],"the":[41,67,72,89,97,105,130],"information":[42],"on":[43,88,116],"problems.":[45],"paper,":[48],"we":[49,82],"propose":[50],"method":[52,113,124],"that":[53],"samples":[54],"with":[56,61,78,108,129],"L\u00e9vy":[58,109],"distribution":[59],"together":[60],"sorting":[64,80],"step":[70],"of":[71,91],"proposed":[73,112],"method,":[74],"sorted":[77,106],"algorithm":[81],"proposed,":[83],"which":[84],"sorts":[85],"based":[87],"likelihood":[90],"being":[95],"inlier":[98],"set.":[99],"Then,":[100],"hypotheses":[101],"are":[102],"from":[104],"distribution.":[110],"The":[111],"evaluated":[115],"both":[117],"simulation":[118],"real-world":[120],"public":[121],"datasets.":[122],"Our":[123],"shows":[125],"better":[126],"results":[127],"compared":[128],"baseline":[132],"method.":[133]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}