{"id":"https://openalex.org/W1510481520","doi":"https://doi.org/10.2312/spbg/spbg04/193-199","title":"Shape Segmentation and Matching from Noisy Point Clouds","display_name":"Shape Segmentation and Matching from Noisy Point Clouds","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W1510481520","doi":"https://doi.org/10.2312/spbg/spbg04/193-199","mag":"1510481520"},"language":"en","primary_location":{"id":"doi:10.2312/spbg/spbg04/193-199","is_oa":true,"landing_page_url":"https://doi.org/10.2312/spbg/spbg04/193-199","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/spbg/spbg04/193-199","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025354167","display_name":"Tamal K. Dey","orcid":"https://orcid.org/0000-0001-5160-9738"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dey, Tamal K.","raw_affiliation_strings":["The Ohio State U.;"],"affiliations":[{"raw_affiliation_string":"The Ohio State U.;","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027313464","display_name":"Joachim Giesen","orcid":"https://orcid.org/0000-0001-6598-6833"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Giesen, Joachim","raw_affiliation_strings":["[ETH, Zurich]"],"affiliations":[{"raw_affiliation_string":"[ETH, Zurich]","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115589047","display_name":"Samrat Goswami","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Goswami, Samrat","raw_affiliation_strings":["The Ohio State U.;"],"affiliations":[{"raw_affiliation_string":"The Ohio State U.;","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025354167"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9994999766349792,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9994999766349792,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9990000128746033,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9976999759674072,"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/delaunay-triangulation","display_name":"Delaunay triangulation","score":0.890998363494873},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7062424421310425},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.674656331539154},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6095818281173706},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5685610771179199},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5423018336296082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5392128229141235},{"id":"https://openalex.org/keywords/point-distribution-model","display_name":"Point distribution model","score":0.5229126214981079},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5210599303245544},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.47609055042266846},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4716165363788605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46017494797706604},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4594346880912781},{"id":"https://openalex.org/keywords/triangulation","display_name":"Triangulation","score":0.4531044661998749},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4514261782169342},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43779605627059937},{"id":"https://openalex.org/keywords/constrained-delaunay-triangulation","display_name":"Constrained Delaunay triangulation","score":0.41798773407936096},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4175349473953247},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37396758794784546},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.2100973129272461},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.11823943257331848}],"concepts":[{"id":"https://openalex.org/C68010082","wikidata":"https://www.wikidata.org/wiki/Q192445","display_name":"Delaunay triangulation","level":2,"score":0.890998363494873},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7062424421310425},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.674656331539154},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6095818281173706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5685610771179199},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5423018336296082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5392128229141235},{"id":"https://openalex.org/C118317068","wikidata":"https://www.wikidata.org/wiki/Q2100760","display_name":"Point distribution model","level":2,"score":0.5229126214981079},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5210599303245544},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.47609055042266846},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4716165363788605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46017494797706604},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4594346880912781},{"id":"https://openalex.org/C135981907","wikidata":"https://www.wikidata.org/wiki/Q188056","display_name":"Triangulation","level":2,"score":0.4531044661998749},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4514261782169342},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43779605627059937},{"id":"https://openalex.org/C128321387","wikidata":"https://www.wikidata.org/wiki/Q5164356","display_name":"Constrained Delaunay triangulation","level":3,"score":0.41798773407936096},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4175349473953247},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37396758794784546},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.2100973129272461},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.11823943257331848},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2312/spbg/spbg04/193-199","is_oa":true,"landing_page_url":"https://doi.org/10.2312/spbg/spbg04/193-199","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.2312/spbg/spbg04/193-199","is_oa":true,"landing_page_url":"https://doi.org/10.2312/spbg/spbg04/193-199","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1481521171","https://openalex.org/W1809711019","https://openalex.org/W1972159725","https://openalex.org/W1992446047","https://openalex.org/W2057175746","https://openalex.org/W2083485913","https://openalex.org/W2088352159","https://openalex.org/W2099606917","https://openalex.org/W2108611942","https://openalex.org/W2128012088","https://openalex.org/W2160754664","https://openalex.org/W2160994953","https://openalex.org/W2165649407","https://openalex.org/W2165939338","https://openalex.org/W3139497334"],"related_works":["https://openalex.org/W1809711019","https://openalex.org/W305281390","https://openalex.org/W2562921071","https://openalex.org/W2033943689","https://openalex.org/W1503891568","https://openalex.org/W2937426451","https://openalex.org/W2728326942","https://openalex.org/W2162450071","https://openalex.org/W2971857908","https://openalex.org/W2902879299","https://openalex.org/W2107869668","https://openalex.org/W2003069013","https://openalex.org/W45164898","https://openalex.org/W2096330154","https://openalex.org/W1506759263","https://openalex.org/W2790682573","https://openalex.org/W2019180344","https://openalex.org/W1935327309","https://openalex.org/W40265707","https://openalex.org/W1973375368"],"abstract_inverted_index":{"We":[0],"present":[1],"the":[2,23,33,40,43,66,70,75,79,90,103,106],"implementation":[3],"results":[4,101],"of":[5,42,46,69,84,105],"a":[6,19,62],"shape":[7,13,44],"segmentation":[8],"technique":[9],"and":[10,55,73],"an":[11],"associated":[12],"matching":[14],"method":[15,107],"whose":[16],"input":[17],"is":[18,27,53],"point":[20,71],"sample":[21,26],"from":[22,89],"shape.":[24],"The":[25,51],"allowed":[28],"to":[29,77,97],"be":[30],"noisy":[31],"in":[32,58,108],"sense":[34],"that":[35,59],"they":[36],"may":[37],"scatter":[38],"around":[39],"boundary":[41],"instead":[45],"lying":[47],"exactly":[48],"on":[49],"it.":[50],"algorithm":[52],"simple":[54],"mostly":[56],"combinatorial":[57],"it":[60],"builds":[61],"single":[63],"data":[64],"structure,":[65],"Delaunay":[67],"triangulation":[68],"set,":[72],"groups":[74],"tetrahedra":[76],"form":[78],"segments.":[80],"A":[81],"small":[82],"set":[83],"weighted":[85],"points":[86],"are":[87,93],"derived":[88],"segments":[91],"which":[92],"used":[94],"as":[95],"signatures":[96],"match":[98],"shapes.":[99],"Experimental":[100],"establish":[102],"effectiveness":[104],"practice.":[109]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}