{"id":"https://openalex.org/W2028125943","doi":"https://doi.org/10.1145/2425836.2425896","title":"High-throughput 3D modelling of plants for phenotypic analysis","display_name":"High-throughput 3D modelling of plants for phenotypic analysis","publication_year":2012,"publication_date":"2012-11-26","ids":{"openalex":"https://openalex.org/W2028125943","doi":"https://doi.org/10.1145/2425836.2425896","mag":"2028125943"},"language":"en","primary_location":{"id":"doi:10.1145/2425836.2425896","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2425836.2425896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Conference on Image and Vision Computing New Zealand","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/A5101527876","display_name":"Pankaj Kumar","orcid":"https://orcid.org/0000-0002-9646-1244"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Pankaj Kumar","raw_affiliation_strings":["University of South Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036994322","display_name":"Jinhai Cai","orcid":"https://orcid.org/0000-0002-7298-1579"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jinhai Cai","raw_affiliation_strings":["University of South Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047243168","display_name":"Stanley J. Miklavcic","orcid":"https://orcid.org/0000-0002-2361-246X"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Stan Miklavcic","raw_affiliation_strings":["University of South Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Australia","institution_ids":["https://openalex.org/I170239107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170239107"],"apc_list":null,"apc_paid":null,"fwci":2.8284,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.90212188,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"301","last_page":"306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9961000084877014,"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/throughput","display_name":"Throughput","score":0.7093420624732971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5806704163551331},{"id":"https://openalex.org/keywords/phenotype","display_name":"Phenotype","score":0.42923590540885925},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.17239555716514587},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.1007067859172821},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06715169548988342}],"concepts":[{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.7093420624732971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5806704163551331},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.42923590540885925},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.17239555716514587},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.1007067859172821},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06715169548988342},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2425836.2425896","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2425836.2425896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Conference on Image and Vision Computing New Zealand","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":15,"referenced_works":["https://openalex.org/W193066332","https://openalex.org/W1486632395","https://openalex.org/W1554663460","https://openalex.org/W1885010708","https://openalex.org/W2069615085","https://openalex.org/W2069818618","https://openalex.org/W2080789762","https://openalex.org/W2107295961","https://openalex.org/W2109131581","https://openalex.org/W2111223858","https://openalex.org/W2119391667","https://openalex.org/W2124135873","https://openalex.org/W2127673637","https://openalex.org/W2132728200","https://openalex.org/W2561675875"],"related_works":["https://openalex.org/W2625512991","https://openalex.org/W2526884355","https://openalex.org/W1002902646","https://openalex.org/W2381241007","https://openalex.org/W2621281690","https://openalex.org/W2950363298","https://openalex.org/W2041947271","https://openalex.org/W2017976553","https://openalex.org/W2090361819","https://openalex.org/W2041649478"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"propose":[4,119],"a":[5,120,127,138,150,195],"twin":[6],"mirror-based":[7],"system":[8],"for":[9,16],"reconstructing":[10],"3D":[11,189,204],"models":[12,190],"of":[13,31,40,54,67,70,85,95,112,188,191],"real":[14],"plants":[15],"subsequent":[17],"phenotypic":[18],"analysis.":[19],"The":[20,51,132],"method":[21],"is":[22,61,169],"based":[23],"on":[24,65],"the":[25,32,35,41,55,68,71,77,96,113,116,144,166,173,178,200],"visual":[26,205],"hull":[27,106,206],"concept:":[28],"multiple":[29],"reflections":[30,60],"object":[33,42,56,86,114],"from":[34,48,115,129,182],"mirrors":[36],"give":[37,89],"different":[38,91],"views":[39,94],"and":[43,57,73,92,175,194,203],"are":[44,108,135,147],"interpreted":[45],"as":[46],"taken":[47],"virtual":[49],"cameras.":[50],"epipolar":[52],"geometry":[53],"its":[58,130],"four":[59],"determined":[62],"without":[63,98],"relying":[64],"information":[66],"positions":[69],"camera":[72,79,103],"mirrors.":[74],"This":[75],"alleviates":[76],"usual":[78],"calibration":[80],"step.":[81],"Two":[82],"simultaneous":[83,93],"images":[84],"mirror":[87],"scene":[88],"ten":[90],"plant,":[97],"requiring":[99],"any":[100],"plant":[101,128,133,180],"or":[102],"movement.":[104],"Visual":[105],"algorithms":[107],"sensitive":[109],"to":[110,125,171],"segmentation":[111,202],"scene.":[117],"We":[118,185],"novel":[121],"machine":[122],"learning":[123],"approach":[124],"segment":[126,177],"background.":[131],"colours":[134,146],"represented":[136,148],"using":[137,154,199],"Gaussian":[139],"mixture":[140],"model":[141],"(GMM),":[142],"while":[143],"background":[145],"by":[149],"separate":[151],"GMM,":[152],"learnt":[153],"an":[155],"Expectation":[156],"Maximisation":[157],"(EM)":[158],"algorithm.":[159],"A":[160],"Bayes":[161],"classification":[162],"rule":[163],"that":[164],"satisfies":[165],"Neymann-Pearson":[167],"criteria":[168],"used":[170],"classify":[172],"pixels":[174],"thus":[176],"five":[179],"silhouette":[181],"each":[183],"image.":[184],"show":[186],"results":[187],"wheat,":[192],"grass,":[193],"lavender":[196],"shoot":[197],"reconstructed":[198],"proposed":[201],"method.":[207]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}