{"id":"https://openalex.org/W4401417222","doi":"https://doi.org/10.1109/icra57147.2024.10611029","title":"Multi-Object RANSAC: Efficient Plane Clustering Method in a Clutter","display_name":"Multi-Object RANSAC: Efficient Plane Clustering Method in a Clutter","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4401417222","doi":"https://doi.org/10.1109/icra57147.2024.10611029"},"language":"en","primary_location":{"id":"doi:10.1109/icra57147.2024.10611029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5042755827","display_name":"SeungHyeon Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seunghyeon Lim","raw_affiliation_strings":["Seoul National University,Interdisciplinary Program in Cognitive Science,Seoul,Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Interdisciplinary Program in Cognitive Science,Seoul,Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039380804","display_name":"Youngjae Yoo","orcid":"https://orcid.org/0000-0003-3276-389X"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngjae Yoo","raw_affiliation_strings":["Seoul National University,Department of Computer Science and Engineering,Seoul,Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Computer Science and Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000065115","display_name":"Jun Ki Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jun Ki Lee","raw_affiliation_strings":["AIIS, Seoul National University,Seoul,Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AIIS, Seoul National University,Seoul,Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110207888","display_name":"Byoung-Tak Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byoung-Tak Zhang","raw_affiliation_strings":["Seoul National University,Interdisciplinary Program in Cognitive Science,Seoul,Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Interdisciplinary Program in Cognitive Science,Seoul,Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":8.1894,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.97827857,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3079","last_page":"3085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9983000159263611,"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":0.9983000159263611,"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/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9925000071525574,"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":0.9606946110725403},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.7884383201599121},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7258304357528687},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6568788290023804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6520028114318848},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5801569223403931},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5377683043479919},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3206818997859955},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.0921718180179596},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07857832312583923}],"concepts":[{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.9606946110725403},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.7884383201599121},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7258304357528687},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6568788290023804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6520028114318848},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5801569223403931},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5377683043479919},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3206818997859955},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0921718180179596},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07857832312583923},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra57147.2024.10611029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra57147.2024.10611029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1923184257","https://openalex.org/W1972630525","https://openalex.org/W2000018820","https://openalex.org/W2021851106","https://openalex.org/W2036470408","https://openalex.org/W2058535340","https://openalex.org/W2079448160","https://openalex.org/W2085261163","https://openalex.org/W2088485134","https://openalex.org/W2180058017","https://openalex.org/W2566705929","https://openalex.org/W2781826143","https://openalex.org/W2786036844","https://openalex.org/W2895823395","https://openalex.org/W2905260191","https://openalex.org/W2962828767","https://openalex.org/W2963121255","https://openalex.org/W2964239605","https://openalex.org/W2967153639","https://openalex.org/W2967414433","https://openalex.org/W2967756832","https://openalex.org/W2973390148","https://openalex.org/W2987672160","https://openalex.org/W2988715931","https://openalex.org/W3025669527","https://openalex.org/W3034373437","https://openalex.org/W3034424919","https://openalex.org/W3087607228","https://openalex.org/W3099587965","https://openalex.org/W3202948970","https://openalex.org/W4312654682","https://openalex.org/W4312876407","https://openalex.org/W6638667902","https://openalex.org/W6739778489","https://openalex.org/W6747827861","https://openalex.org/W6789211778"],"related_works":["https://openalex.org/W2131378265","https://openalex.org/W2984240274","https://openalex.org/W3107042705","https://openalex.org/W2981196697","https://openalex.org/W3083084699","https://openalex.org/W2115876589","https://openalex.org/W3012182724","https://openalex.org/W1988708904","https://openalex.org/W2091196744","https://openalex.org/W2039208430"],"abstract_inverted_index":{"In":[0],"this":[1,132],"paper,":[2],"we":[3],"propose":[4],"a":[5,45,90],"novel":[6],"method":[7,121],"for":[8,146],"plane":[9,55,102],"clustering":[10],"specialized":[11],"in":[12,60,89],"cluttered":[13,41],"scenes":[14],"using":[15,93],"an":[16,113],"RGB-D":[17],"camera":[18],"and":[19,126,150],"validate":[20],"its":[21,136,144],"effectiveness":[22],"through":[23],"robot":[24,116],"grasping":[25,124],"experiments.":[26],"Unlike":[27],"existing":[28],"methods,":[29,142],"which":[30,66],"focus":[31],"on":[32,115],"large-":[33],"scale":[34],"indoor":[35],"structures,":[36],"our":[37,120],"approach\u2014Multi-Object":[38],"RANSAC":[39,99,109,127],"emphasizes":[40],"environments":[42],"that":[43],"contain":[44],"wide":[46],"range":[47],"of":[48],"objects":[49],"with":[50,70,122],"different":[51],"scales.":[52],"It":[53],"enhances":[54],"segmentation":[56,104],"by":[57,74,81],"generating":[58],"subplanes":[59],"Deep":[61],"Plane":[62],"Clustering":[63],"(DPC)":[64],"module,":[65],"are":[67],"then":[68],"merged":[69],"the":[71,78,140],"final":[72],"planes":[73],"postprocessing.":[75],"DPC":[76],"rearranges":[77],"point":[79],"cloud":[80],"voting":[82],"layers":[83],"to":[84],"make":[85],"subplane":[86],"clusters,":[87],"trained":[88],"self-supervised":[91],"manner":[92],"pseudo-labels":[94],"generated":[95],"from":[96,131],"RANSAC.":[97],"Multi-Object":[98],"demonstrates":[100],"superior":[101],"instance":[103],"performances":[105],"over":[106],"other":[107],"recent":[108],"applications.":[110,128],"We":[111],"conducted":[112],"experiment":[114],"suction-based":[117],"grasping,":[118],"comparing":[119],"vision-based":[123],"network":[125],"The":[129],"results":[130],"real-world":[133],"scenario":[134],"showed":[135],"remarkable":[137],"performance":[138],"surpassing":[139],"baseline":[141],"highlighting":[143],"potential":[145],"advanced":[147],"scene":[148],"understanding":[149],"manipulation.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}