{"id":"https://openalex.org/W4241032814","doi":"https://doi.org/10.1504/ijma.2018.10015627","title":"Verification of unique cloth handling performance based on 3D recognition accuracy of cloth by dual-eyes cameras with photo-model-based matching","display_name":"Verification of unique cloth handling performance based on 3D recognition accuracy of cloth by dual-eyes cameras with photo-model-based matching","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W4241032814","doi":"https://doi.org/10.1504/ijma.2018.10015627"},"language":"en","primary_location":{"id":"doi:10.1504/ijma.2018.10015627","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijma.2018.10015627","pdf_url":null,"source":{"id":"https://openalex.org/S4306424363","display_name":"International Journal of Mechatronics and Automation","issn_l":"2045-1059","issn":["2045-1059","2045-1067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Mechatronics and Automation","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/A5075689358","display_name":"Khaing Win Phyu","orcid":null},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Khaing Win Phyu","raw_affiliation_strings":["Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan","institution_ids":["https://openalex.org/I163770644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110261450","display_name":"Mamoru Minami","orcid":null},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mamoru Minami","raw_affiliation_strings":["Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan","institution_ids":["https://openalex.org/I163770644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071296973","display_name":"Fumiya Ikegawa","orcid":null},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fumiya Ikegawa","raw_affiliation_strings":["Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan","institution_ids":["https://openalex.org/I163770644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014075181","display_name":"Ryuki Funakubo","orcid":null},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryuki Funakubo","raw_affiliation_strings":["Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Natural Science and Technology, Okayama University, 3-1-1, Tsushimanaka, Kita-ku, Okayama, 700-8530, Japan","institution_ids":["https://openalex.org/I163770644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44971334,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"2/3","first_page":"55","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10531","display_name":"Advanced Vision and Imaging","score":0.9192000031471252,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9160000085830688,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7504022121429443},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7374852895736694},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6388599276542664},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6029552817344666},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5716339349746704},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5384286642074585},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5329782962799072},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5144631862640381},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.45859992504119873},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.41561025381088257},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.41494399309158325},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3473978638648987},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11216402053833008},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06667682528495789}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7504022121429443},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7374852895736694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6388599276542664},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6029552817344666},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5716339349746704},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5384286642074585},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5329782962799072},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5144631862640381},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.45859992504119873},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.41561025381088257},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.41494399309158325},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3473978638648987},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11216402053833008},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06667682528495789},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijma.2018.10015627","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijma.2018.10015627","pdf_url":null,"source":{"id":"https://openalex.org/S4306424363","display_name":"International Journal of Mechatronics and Automation","issn_l":"2045-1059","issn":["2045-1059","2045-1067"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Mechatronics and Automation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1972035260","https://openalex.org/W2317351040","https://openalex.org/W4285447065","https://openalex.org/W1988622314","https://openalex.org/W2393949104","https://openalex.org/W2794488505","https://openalex.org/W3046201198","https://openalex.org/W4301594054","https://openalex.org/W4293061921","https://openalex.org/W2952466936"],"abstract_inverted_index":{"Nowadays,":[0],"innovative":[1],"robotic":[2],"technology":[3],"has":[4,138],"been":[5,14,139],"implemented":[6],"in":[7,18,39],"the":[8,31,36,42,46,106,111,125,143],"garment":[9],"companies.":[10],"However,":[11],"robots":[12],"have":[13],"confronted":[15],"with":[16],"difficulties":[17],"recognising":[19],"and":[20,52,55,71,86,109,131],"handling":[21,72,127,136],"deformable":[22],"object":[23,32],"such":[24],"as":[25],"cloth,":[26],"string":[27],"etc.,":[28],"especially":[29],"if":[30],"is":[33,44,121],"unique.":[34],"Specifically,":[35],"cloth":[37,69,84,108,115,148],"placed":[38],"front":[40],"of":[41,113,145],"robot":[43],"rightly":[45],"intended":[47],"one":[48],"to":[49,53,104,123],"be":[50],"handled":[51],"pick":[54],"place":[56],"(handle)":[57],"at":[58],"a":[59,75],"designated":[60],"position":[61,130],"automatically":[62],"are":[63,96],"two":[64],"main":[65],"problems":[66],"during":[67],"3D":[68,126],"recognition":[70,149],"performance":[73],"by":[74],"robot.":[76],"In":[77],"this":[78],"paper,":[79],"model":[80],"generation":[81],"method":[82,89],"from":[83],"photograph":[85],"model-based":[87],"matching":[88],"(recognition":[90],"method)":[91],"utilising":[92],"Genetic":[93],"Algorithm":[94],"(GA)":[95],"presented.":[97],"The":[98,118],"proposed":[99,119,146],"system":[100,120],"uses":[101],"dual-eyes":[102],"cameras":[103],"recognise":[105],"target":[107],"estimate":[110],"pose":[112],"that":[114],"for":[116],"handling.":[117],"used":[122],"verify":[124],"under":[128],"predetermining":[129],"orientation":[132],"range.":[133],"100":[134],"times":[135],"experiment":[137],"executed,":[140],"having":[141],"shown":[142],"effectiveness":[144],"photo-model-based":[147],"system.":[150]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
