{"id":"https://openalex.org/W4403676549","doi":"https://doi.org/10.1109/case59546.2024.10711641","title":"Comparative Study of Keypoint Detection and ArUco Marker Methods for Optical 6D Pose Estimation in Electronics Packaging","display_name":"Comparative Study of Keypoint Detection and ArUco Marker Methods for Optical 6D Pose Estimation in Electronics Packaging","publication_year":2024,"publication_date":"2024-08-28","ids":{"openalex":"https://openalex.org/W4403676549","doi":"https://doi.org/10.1109/case59546.2024.10711641"},"language":"en","primary_location":{"id":"doi:10.1109/case59546.2024.10711641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case59546.2024.10711641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","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/A5052838413","display_name":"Lucas Janisch","orcid":"https://orcid.org/0000-0002-2936-7207"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lucas Janisch","raw_affiliation_strings":["Friedrich-Alexander Universität Erlangen-Nürnberg,Institute for Factory Automation and Production Systems,Nuremberg,Germany,90429"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander Universität Erlangen-Nürnberg,Institute for Factory Automation and Production Systems,Nuremberg,Germany,90429","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058354067","display_name":"Daniel Schulz","orcid":"https://orcid.org/0009-0006-5712-3919"},"institutions":[{"id":"https://openalex.org/I4210142109","display_name":"Rosenheim Technical University of Applied Sciences","ror":"https://ror.org/03hbmgt12","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210142109"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Schulz","raw_affiliation_strings":["Technische Hochschule Rosenheim,Department of Informatics,Rosenheim,Germany,83024"],"affiliations":[{"raw_affiliation_string":"Technische Hochschule Rosenheim,Department of Informatics,Rosenheim,Germany,83024","institution_ids":["https://openalex.org/I4210142109"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101598681","display_name":"Alexander Schmidt","orcid":"https://orcid.org/0000-0003-3364-901X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alexander Schmidt","raw_affiliation_strings":["Friedrich-Alexander Universität Erlangen-Nürnberg,Institute for Factory Automation and Production Systems,Nuremberg,Germany,90429"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander Universität Erlangen-Nürnberg,Institute for Factory Automation and Production Systems,Nuremberg,Germany,90429","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020059878","display_name":"Raven T. Reisch","orcid":"https://orcid.org/0000-0002-0602-1705"},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Raven Reisch","raw_affiliation_strings":["Siemens AG, Technology,Munich,Germany,81739"],"affiliations":[{"raw_affiliation_string":"Siemens AG, Technology,Munich,Germany,81739","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085229340","display_name":"Tobias Kamps","orcid":null},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias Kamps","raw_affiliation_strings":["Siemens AG, Technology,Munich,Germany,81739"],"affiliations":[{"raw_affiliation_string":"Siemens AG, Technology,Munich,Germany,81739","institution_ids":["https://openalex.org/I1325886976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101872791","display_name":"J\u00f6rg Franke","orcid":"https://orcid.org/0000-0001-7897-4225"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"J\u00f6rg Franke","raw_affiliation_strings":["Friedrich-Alexander Universität Erlangen-Nürnberg,Institute for Factory Automation and Production Systems,Nuremberg,Germany,90429"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander Universität Erlangen-Nürnberg,Institute for Factory Automation and Production Systems,Nuremberg,Germany,90429","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5052838413"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2632,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.553474,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3969","last_page":"3974"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9943000078201294,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9943000078201294,"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/T13579","display_name":"Image and Video Stabilization","score":0.9921000003814697,"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.9850999712944031,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.645672082901001},{"id":"https://openalex.org/keywords/electronics","display_name":"Electronics","score":0.5529747009277344},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5105353593826294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.496568500995636},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3814704418182373},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2341008186340332},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.14883604645729065}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.645672082901001},{"id":"https://openalex.org/C138331895","wikidata":"https://www.wikidata.org/wiki/Q11650","display_name":"Electronics","level":2,"score":0.5529747009277344},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5105353593826294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.496568500995636},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3814704418182373},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2341008186340332},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.14883604645729065}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case59546.2024.10711641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case59546.2024.10711641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","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":29,"referenced_works":["https://openalex.org/W1508568262","https://openalex.org/W1994349244","https://openalex.org/W2008396203","https://openalex.org/W2058761328","https://openalex.org/W2071349155","https://openalex.org/W2083736156","https://openalex.org/W2151103935","https://openalex.org/W2164139712","https://openalex.org/W2604236302","https://openalex.org/W2950921159","https://openalex.org/W2963150697","https://openalex.org/W2963542378","https://openalex.org/W2964208152","https://openalex.org/W2964249569","https://openalex.org/W2981854237","https://openalex.org/W3033644306","https://openalex.org/W3045888475","https://openalex.org/W3108069550","https://openalex.org/W3134814607","https://openalex.org/W3177069133","https://openalex.org/W4231592725","https://openalex.org/W4283822591","https://openalex.org/W4323349553","https://openalex.org/W4378574606","https://openalex.org/W4379985979","https://openalex.org/W4389432282","https://openalex.org/W4390481045","https://openalex.org/W6628898621","https://openalex.org/W6803376173"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,130],"push":[1],"for":[2,26],"miniaturization":[3],"and":[4,36,84,91,149,158,173,192],"functional":[5],"integration":[6],"in":[7,58,123,144,168,170],"electronics":[8],"packaging":[9],"is":[10],"driving":[11],"the":[12,33,76,121,128,134,147,156,161,171,176,187,190],"adoption":[13],"of":[14,38,52,55,60,96,120,194],"increasingly":[15],"complex":[16],"three-dimensional":[17],"designs,":[18],"necessitating":[19],"advanced":[20],"optical":[21,41,70],"6D":[22,195],"Pose":[23,196],"Estimation":[24,197],"techniques":[25,98],"precise":[27,46,110],"automated":[28],"manufacturing.":[29],"This":[30],"study":[31,188],"covers":[32],"development,":[34],"investigation,":[35],"comparison":[37],"two":[39],"distinct":[40],"approaches":[42],"aimed":[43],"at":[44],"achieving":[45],"pose":[47,118],"detection":[48],"with":[49,139,183],"six":[50,124],"degrees":[51],"freedom":[53],"(6-DoF)":[54],"electronic":[56],"components,":[57],"particular":[59],"Direct":[61],"Bonded":[62],"Copper":[63],"substrates.":[64],"One":[65],"method":[66],"involved":[67],"using":[68],"laser-engraved":[69],"markers":[71],"(specifically":[72],"ArUco":[73],"Markers),":[74],"while":[75,115],"other":[77],"relied":[78],"on":[79,88],"Keypoint":[80,135],"Detection,":[81],"utilizing":[82],"YOLOv8":[83],"Mask":[85],"R-CNN":[86],"trained":[87],"both":[89],"real":[90],"synthetic":[92],"data.":[93],"Performance":[94],"evaluation":[95],"these":[97],"was":[99],"conducted":[100],"by":[101],"engineering":[102],"a":[103,179],"novel":[104],"vision":[105],"setup":[106],"designed":[107],"to":[108,127,202],"maintain":[109],"control":[111],"over":[112],"lighting":[113],"conditions":[114],"facilitating":[116],"accurate":[117],"adjustments":[119],"probe":[122],"dimensions":[125],"relative":[126],"camera.":[129],"analysis":[131,181],"revealed":[132],"that":[133],"Detection":[136],"method,":[137],"particularly":[138,199],"YOLOv8,":[140],"exhibited":[141],"superior":[142],"accuracy":[143,167],"translation":[145,169],"along":[146],"x-":[148,157],"y-directions,":[150],"as":[151,153],"well":[152],"rotation":[154,174],"around":[155,175],"y-axes.":[159],"Conversely,":[160],"marker-based":[162],"approach":[163],"demonstrated":[164],"significantly":[165],"higher":[166],"z-direction":[172],"z-axis.":[177],"Through":[178],"qualitative":[180],"coupled":[182],"extensive":[184],"quantitative":[185],"evaluation,":[186],"reveals":[189],"strengths":[191],"weaknesses":[193],"methods,":[198],"when":[200],"applied":[201],"miniature":[203],"copper":[204],"components.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}