{"id":"https://openalex.org/W3086736791","doi":"https://doi.org/10.1109/lsp.2020.3023587","title":"Hypergraph Spectral Clustering for Point Cloud Segmentation","display_name":"Hypergraph Spectral Clustering for Point Cloud Segmentation","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3086736791","doi":"https://doi.org/10.1109/lsp.2020.3023587","mag":"3086736791"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.3023587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3023587","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5100747791","display_name":"Songyang Zhang","orcid":"https://orcid.org/0000-0002-2895-5728"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Songyang Zhang","raw_affiliation_strings":["Department of Electrical, and Computer Engineering, University of California at Davis, Davis, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2895-5728","affiliations":[{"raw_affiliation_string":"Department of Electrical, and Computer Engineering, University of California at Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009164482","display_name":"Shuguang Cui","orcid":"https://orcid.org/0000-0003-2608-775X"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuguang Cui","raw_affiliation_strings":["Shenzhen Research Institute of Big Data, and Future Network of Intelligence Institute (FNii), the Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2608-775X","affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, and Future Network of Intelligence Institute (FNii), the Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085794086","display_name":"Zhi Ding","orcid":"https://orcid.org/0000-0002-2649-2125"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhi Ding","raw_affiliation_strings":["Department of Electrical, and Computer Engineering, University of California at Davis, Davis, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2649-2125","affiliations":[{"raw_affiliation_string":"Department of Electrical, and Computer Engineering, University of California at Davis, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6966,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.90434461,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"27","issue":null,"first_page":"1655","last_page":"1659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9925000071525574,"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":0.9925000071525574,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9824000000953674,"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":0.9763000011444092,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.8567181825637817},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.840256929397583},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.7336458563804626},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7103464007377625},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6124153733253479},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5416153073310852},{"id":"https://openalex.org/keywords/spectral-space","display_name":"Spectral space","score":0.5101380944252014},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4797447919845581},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4584618806838989},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45239323377609253},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37947067618370056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36834025382995605},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3470584750175476},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.07164826989173889}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.8567181825637817},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.840256929397583},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.7336458563804626},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7103464007377625},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6124153733253479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5416153073310852},{"id":"https://openalex.org/C2778740170","wikidata":"https://www.wikidata.org/wiki/Q7575210","display_name":"Spectral space","level":2,"score":0.5101380944252014},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4797447919845581},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4584618806838989},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45239323377609253},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37947067618370056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36834025382995605},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3470584750175476},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.07164826989173889},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2020.3023587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3023587","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1944879398","display_name":null,"funder_award_id":"1824553","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1590776313","https://openalex.org/W1978376511","https://openalex.org/W1986473362","https://openalex.org/W2001303383","https://openalex.org/W2005276292","https://openalex.org/W2059827653","https://openalex.org/W2068078373","https://openalex.org/W2089466286","https://openalex.org/W2121947440","https://openalex.org/W2127486527","https://openalex.org/W2132914434","https://openalex.org/W2152864241","https://openalex.org/W2155074104","https://openalex.org/W2161494102","https://openalex.org/W2165874743","https://openalex.org/W2170057991","https://openalex.org/W2185278568","https://openalex.org/W2190691619","https://openalex.org/W2237805507","https://openalex.org/W2299462150","https://openalex.org/W2541785124","https://openalex.org/W2591997370","https://openalex.org/W2624256161","https://openalex.org/W2765731028","https://openalex.org/W2780029264","https://openalex.org/W2788730170","https://openalex.org/W2796431263","https://openalex.org/W2799629938","https://openalex.org/W2951187577","https://openalex.org/W2962759781","https://openalex.org/W2963384510","https://openalex.org/W2963414755","https://openalex.org/W2963702033","https://openalex.org/W2963830382","https://openalex.org/W2964012239","https://openalex.org/W2965585318","https://openalex.org/W2992026644","https://openalex.org/W2994097903","https://openalex.org/W3000467754","https://openalex.org/W3002899590","https://openalex.org/W3021387581","https://openalex.org/W3100282875","https://openalex.org/W3105663757","https://openalex.org/W4394671432","https://openalex.org/W6684578312","https://openalex.org/W6685083254","https://openalex.org/W6686975262","https://openalex.org/W6687484953","https://openalex.org/W6729517626","https://openalex.org/W6745213692","https://openalex.org/W6772646543"],"related_works":["https://openalex.org/W2914946164","https://openalex.org/W2792371717","https://openalex.org/W3100018624","https://openalex.org/W2181697047","https://openalex.org/W3126089168","https://openalex.org/W3086736791","https://openalex.org/W3002899590","https://openalex.org/W1599474586","https://openalex.org/W2541785124","https://openalex.org/W2142009282"],"abstract_inverted_index":{"Hypergraph":[0],"spectral":[1,46,75,79,101],"analysis":[2,47],"has":[3],"emerged":[4],"as":[5],"an":[6],"effective":[7],"tool":[8],"processing":[9],"complex":[10],"data":[11,14],"structures":[12],"in":[13,48],"analysis.":[15],"The":[16],"surface":[17],"of":[18,44,51,111],"a":[19,84],"three-dimensional":[20],"(3D)":[21],"point":[22,53,64,95],"cloud,":[23],"and":[24,57,97,109],"the":[25,36,42,59,69,72,90,107,112],"multilateral":[26],"relationship":[27],"among":[28],"their":[29,99],"points":[30],"can":[31],"be":[32],"naturally":[33],"captured":[34],"by":[35],"high-dimensional":[37],"hyperedges.":[38],"This":[39],"work":[40],"investigates":[41],"power":[43],"hypergraph":[45,60,74],"unsupervised":[49],"segmentation":[50,86,114],"3D":[52],"clouds.":[54],"We":[55,88],"estimate,":[56],"order":[58],"spectrum":[61],"from":[62,71],"observed":[63],"cloud":[65],"coordinates.":[66],"By":[67],"trimming":[68],"redundancy":[70],"estimated":[73],"space":[76],"based":[77],"on":[78],"component":[80],"strengths,":[81],"we":[82],"develop":[83],"clustering-based":[85],"method.":[87,115],"apply":[89],"proposed":[91,113],"method":[92],"to":[93],"various":[94],"clouds,":[96],"analyze":[98],"respective":[100],"properties.":[102],"Our":[103],"experimental":[104],"results":[105],"demonstrate":[106],"effectiveness":[108],"efficiency":[110]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
