{"id":"https://openalex.org/W2736178335","doi":"https://doi.org/10.1109/ijcnn.2017.7966006","title":"A large-scale multi-pose 3D-RGB object database","display_name":"A large-scale multi-pose 3D-RGB object database","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2736178335","doi":"https://doi.org/10.1109/ijcnn.2017.7966006","mag":"2736178335"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","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/A5009999367","display_name":"Fabian Sachara","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123225","display_name":"Ruhr West University of Applied Sciences","ror":"https://ror.org/02nkxrq89","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210123225"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Sachara","raw_affiliation_strings":["Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany","institution_ids":["https://openalex.org/I4210123225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007542259","display_name":"Finn Handmann","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123225","display_name":"Ruhr West University of Applied Sciences","ror":"https://ror.org/02nkxrq89","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210123225"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Finn Handmann","raw_affiliation_strings":["Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany","institution_ids":["https://openalex.org/I4210123225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054237171","display_name":"Nico Cremer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123225","display_name":"Ruhr West University of Applied Sciences","ror":"https://ror.org/02nkxrq89","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210123225"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nico Cremer","raw_affiliation_strings":["Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany","institution_ids":["https://openalex.org/I4210123225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061544337","display_name":"Thomas Kopinski","orcid":null},"institutions":[{"id":"https://openalex.org/I3130920692","display_name":"South Westphalia University of Applied Sciences","ror":"https://ror.org/04t5phd24","country_code":"DE","type":"education","lineage":["https://openalex.org/I3130920692"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Kopinski","raw_affiliation_strings":["Fachhochschule S\u00fcdwestfalen, Meschede, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fachhochschule S\u00fcdwestfalen, Meschede, Germany","institution_ids":["https://openalex.org/I3130920692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030810660","display_name":"Alexander Gepperth","orcid":"https://orcid.org/0000-0003-2216-7808"},"institutions":[{"id":"https://openalex.org/I201850948","display_name":"Fulda University of Applied Sciences","ror":"https://ror.org/041bz9r75","country_code":"DE","type":"education","lineage":["https://openalex.org/I201850948"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Gepperth","raw_affiliation_strings":["Applied Computer Science, University of Applied Sciences, Fulda, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Computer Science, University of Applied Sciences, Fulda, Germany","institution_ids":["https://openalex.org/I201850948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078414923","display_name":"Uwe Handmann","orcid":"https://orcid.org/0000-0003-1230-9446"},"institutions":[{"id":"https://openalex.org/I4210123225","display_name":"Ruhr West University of Applied Sciences","ror":"https://ror.org/02nkxrq89","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210123225"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Uwe Handmann","raw_affiliation_strings":["Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Ruhr West, University of Applied Sciences, Bottrop, Germany","institution_ids":["https://openalex.org/I4210123225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"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":0.08353096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1326","last_page":"1332"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.8152109384536743},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7263522148132324},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5846723318099976},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5639969110488892},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5520772933959961},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5072281360626221},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5007214546203613},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.498028039932251},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.48514851927757263},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4442101716995239},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.4266563355922699},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3627200722694397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8152109384536743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7263522148132324},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5846723318099976},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5639969110488892},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5520772933959961},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5072281360626221},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5007214546203613},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.498028039932251},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.48514851927757263},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4442101716995239},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.4266563355922699},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3627200722694397},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W2005756025","https://openalex.org/W2021851106","https://openalex.org/W2058761328","https://openalex.org/W2098764590","https://openalex.org/W2098883970","https://openalex.org/W2132878997","https://openalex.org/W2152864241","https://openalex.org/W2156222070","https://openalex.org/W2397854647","https://openalex.org/W2584408017","https://openalex.org/W6679415930","https://openalex.org/W6732853208"],"related_works":["https://openalex.org/W2123263858","https://openalex.org/W3127959533","https://openalex.org/W4387967917","https://openalex.org/W4387968151","https://openalex.org/W4386925306","https://openalex.org/W3132124459","https://openalex.org/W2946083937","https://openalex.org/W2894986065","https://openalex.org/W4299867837","https://openalex.org/W3110557940"],"abstract_inverted_index":{"We":[0],"present":[1,50],"a":[2,15,42],"new":[3],"RGB-D":[4],"database":[5],"for":[6,130],"multi-pose":[7],"object":[8,99,131],"recognition":[9,100],"tasks.":[10],"With":[11],"the":[12,59,103,109,142],"help":[13],"of":[14,22,28,62,82,111],"multi-axis":[16],"rotation":[17],"framework,":[18],"we":[19],"are":[20],"capable":[21],"capturing":[23],"depth":[24],"and":[25,65,79,86],"color":[26],"data":[27,54,71,84,113,155],"arbitrary":[29],"small":[30],"objects":[31],"from":[32,134],"virtually":[33],"any":[34],"viewpoint.":[35],"In":[36],"addition,":[37],"recording":[38],"is":[39,87,121,137,147],"performed":[40],"in":[41,51],"nearly":[43],"lossless":[44],"fashion,":[45],"avoiding":[46],"typical":[47],"bleeding":[48],"artifacts":[49],"related":[52],"reference":[53,70],"bases.":[55,72],"This":[56],"contribution":[57],"presents":[58],"main":[60],"advantages":[61],"our":[63,83,112,135],"setup":[64],"contrasts":[66],"it":[67,74],"against":[68],"other":[69],"Furthermore,":[73],"outlines":[75],"possible":[76],"use":[77],"cases":[78],"application":[80],"scenarios":[81],"set":[85],"complemented":[88],"by":[89],"experiments":[90,107],"with":[91],"standard":[92],"machine":[93],"learning":[94],"techniques":[95],"used":[96],"in,":[97],"e.g.,":[98],"tasks":[101],"within":[102],"robotics":[104],"domain.":[105],"The":[106],"demonstrate":[108],"validity":[110],"base":[114],"as":[115,159,162],"they":[116],"corroborate":[117],"that":[118],"viewpoint":[119],"variance":[120],"indeed":[122],"an":[123],"important":[124],"factor":[125],"to":[126],"take":[127],"into":[128,157],"account":[129,158],"detection,":[132],"which,":[133],"perspective,":[136],"sometimes":[138],"not":[139],"considered":[140],"at":[141],"required":[143],"level.":[144],"Detection":[145],"accuracy":[146],"high":[148],"if":[149],"samples":[150],"can":[151],"be":[152],"trained":[153],"on":[154],"taking":[156],"many":[160],"viewpoints":[161],"possible.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
