{"id":"https://openalex.org/W6907733112","doi":"https://doi.org/10.2312/3dor/3dor09/013-020","title":"SkelTre - Fast Skeletonisation for Imperfect Point Cloud Data of Botanic Trees","display_name":"SkelTre - Fast Skeletonisation for Imperfect Point Cloud Data of Botanic Trees","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W6907733112","doi":"https://doi.org/10.2312/3dor/3dor09/013-020"},"language":"en","primary_location":{"id":"doi:10.2312/3dor/3dor09/013-020","is_oa":true,"landing_page_url":"https://doi.org/10.2312/3dor/3dor09/013-020","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"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":null},"type":"other","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/3dor/3dor09/013-020","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bucksch, Alexander","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bucksch, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Lindenbergh, Roderik C.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lindenbergh, Roderik C.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Menenti, M.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Menenti, M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"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":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8475000262260437},{"id":"https://openalex.org/keywords/laser-scanning","display_name":"Laser scanning","score":0.6672999858856201},{"id":"https://openalex.org/keywords/octree","display_name":"Octree","score":0.6359000205993652},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5004000067710876},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4180000126361847},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4153999984264374},{"id":"https://openalex.org/keywords/k-d-tree","display_name":"k-d tree","score":0.40560001134872437},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.3878999948501587}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8475000262260437},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.6672999858856201},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.6359000205993652},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5004000067710876},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.453000009059906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45019999146461487},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44699999690055847},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.445499986410141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.430400013923645},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C33721204","wikidata":"https://www.wikidata.org/wiki/Q309949","display_name":"k-d tree","level":3,"score":0.40560001134872437},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C195958017","wikidata":"https://www.wikidata.org/wiki/Q1675268","display_name":"Iterative closest point","level":3,"score":0.37709999084472656},{"id":"https://openalex.org/C2779751349","wikidata":"https://www.wikidata.org/wiki/Q1474480","display_name":"Scanner","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C131509275","wikidata":"https://www.wikidata.org/wiki/Q2296387","display_name":"Triangulated irregular network","level":3,"score":0.2542000114917755},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2312/3dor/3dor09/013-020","is_oa":true,"landing_page_url":"https://doi.org/10.2312/3dor/3dor09/013-020","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"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":null}],"best_oa_location":{"id":"doi:10.2312/3dor/3dor09/013-020","is_oa":true,"landing_page_url":"https://doi.org/10.2312/3dor/3dor09/013-020","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":null,"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":null},"sustainable_development_goals":[{"score":0.43757691979408264,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Terrestrial":[0],"laser":[1,23,123],"scanners":[2],"capture":[3],"3D":[4],"geometry":[5],"as":[6],"a":[7,14,22,28,76,94,131,171],"point":[8,25,54,69,116,125,141],"cloud.":[9,117],"This":[10],"paper":[11,86],"reports":[12],"on":[13,122],"new":[15],"algorithm":[16,82],"aiming":[17],"at":[18],"the":[19,103,106,112,115,134,140,145,156,165],"skeletonisation":[20,81],"of":[21,48,88,93,102,111,139],"scanner":[24,124],"cloud,":[26],"representing":[27,127],"botanical":[29],"tree":[30,42],"without":[31],"leafs.":[32],"The":[33,80,118],"resulting":[34],"skeleton":[35,107,113,146],"can":[36],"subsequently":[37],"be":[38,148],"applied":[39],"to":[40,61,65,74,105,144,152,161,168],"obtain":[41],"parameters":[43],"like":[44],"length":[45],"and":[46,67,108,136,158],"diameter":[47],"branches":[49],"for":[50,155,164],"botanic":[51,128],"applications.":[52],"Scanner-produced":[53],"cloud":[55,142],"data":[56],"are":[57,120],"not":[58],"only":[59],"subject":[60],"noise,":[62],"but":[63],"also":[64],"undersampling":[66],"varying":[68],"densities,":[70],"making":[71],"it":[72],"challenging":[73],"extract":[75],"topologically":[77],"correct":[78],"skeleton.":[79],"proposed":[83],"in":[84],"this":[85],"consists":[87],"three":[89],"steps:":[90],"(i)":[91],"extraction":[92],"graph":[95,104],"from":[96,150,159,170],"an":[97],"octree":[98],"organization,":[99],"(ii)":[100],"reduction":[101],"(iii)":[109],"embedding":[110],"into":[114],"results":[119,169],"validated":[121],"clouds":[126],"trees.":[129],"On":[130],"reference":[132],"tree,":[133],"mean":[135,157],"maximal":[137],"distance":[138],"points":[143],"could":[147],"reduced":[149],"1.8":[151],"1.5":[153],"cm":[154,163],"15.6":[160],"10.5":[162],"maximum,":[166],"compared":[167],"previously":[172],"developed":[173],"method.":[174]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
