{"id":"https://openalex.org/W2132894865","doi":"https://doi.org/10.1109/robot.2004.1308061","title":"Using a hybrid of silhouette and range templates for real-time pose estimation","display_name":"Using a hybrid of silhouette and range templates for real-time pose estimation","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2132894865","doi":"https://doi.org/10.1109/robot.2004.1308061","mag":"2132894865"},"language":"en","primary_location":{"id":"doi:10.1109/robot.2004.1308061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2004.1308061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004","raw_type":"proceedings-article"},"type":"conference-paper","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/A5055335781","display_name":"Eric Huber","orcid":null},"institutions":[{"id":"https://openalex.org/I4210140397","display_name":"Metrica (United States)","ror":"https://ror.org/031ffw737","country_code":"US","type":"company","lineage":["https://openalex.org/I4210140397"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"E. Huber","raw_affiliation_strings":["NASA-JSC, Metrica, Inc., Houston, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NASA-JSC, Metrica, Inc., Houston, TX, USA","institution_ids":["https://openalex.org/I4210140397"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007846952","display_name":"K.D. Baker","orcid":"https://orcid.org/0000-0002-6755-1697"},"institutions":[{"id":"https://openalex.org/I4210149382","display_name":"Johnson Space Center","ror":"https://ror.org/04xx4z452","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210124779","https://openalex.org/I4210149382"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. Baker","raw_affiliation_strings":["NASA-Johnson Space Center, Houston, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NASA-Johnson Space Center, Houston, TX, USA","institution_ids":["https://openalex.org/I4210149382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.4748,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.97302607,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1652","last_page":"1657 Vol.2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998000264167786,"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":0.9998000264167786,"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9986000061035156,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.998199999332428,"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/silhouette","display_name":"Silhouette","score":0.9824070930480957},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7941727042198181},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.783940315246582},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7409927845001221},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6794961094856262},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5790089964866638},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.5191011428833008},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.4788360893726349},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4694755971431732},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.45512813329696655},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.45340201258659363},{"id":"https://openalex.org/keywords/template-matching","display_name":"Template matching","score":0.41657668352127075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3666805624961853},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23389974236488342},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12027594447135925},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08738434314727783}],"concepts":[{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.9824070930480957},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7941727042198181},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.783940315246582},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7409927845001221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6794961094856262},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5790089964866638},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.5191011428833008},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.4788360893726349},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4694755971431732},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.45512813329696655},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.45340201258659363},{"id":"https://openalex.org/C158096908","wikidata":"https://www.wikidata.org/wiki/Q3983303","display_name":"Template matching","level":3,"score":0.41657668352127075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3666805624961853},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23389974236488342},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12027594447135925},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08738434314727783},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/robot.2004.1308061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2004.1308061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004","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":8,"referenced_works":["https://openalex.org/W1585873145","https://openalex.org/W1902096989","https://openalex.org/W2072905107","https://openalex.org/W2110427304","https://openalex.org/W2162440713","https://openalex.org/W2570617923","https://openalex.org/W6635110809","https://openalex.org/W6676793639"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W3089306886","https://openalex.org/W2113785214","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4387967917","https://openalex.org/W4312694060","https://openalex.org/W4386075737","https://openalex.org/W4393563475","https://openalex.org/W4382141741"],"abstract_inverted_index":{"Pose":[0],"estimation":[1,180],"is":[2,30,66,129],"a":[3,28,64,156,174,214],"fundamental":[4],"problem":[5],"in":[6,35,219],"machine":[7],"vision.":[8],"Silhouette":[9],"and":[10,44,75,167],"3D":[11,87],"point":[12,88],"matching":[13,48,161,184],"are":[14,195,240],"two":[15],"of":[16,27,56,63,82,120,140,187,206,217],"the":[17,36,40,57,100,118,132,204],"many":[18],"popular":[19],"methods":[20],"for":[21,177,185],"attacking":[22],"this":[23,237],"problem.":[24],"The":[25,61,191],"appearance":[26,62],"silhouette":[29,47,65,160,183],"highly":[31],"sensitive":[32,68],"to":[33,52,69,97,106,130,159],"changes":[34],"object's":[37,125],"planar":[38],"(WRT":[39],"object":[41],"plane)":[42],"location":[43],"orientation.":[45],"Therefore,":[46],"can":[49,94],"be":[50,95,143,150],"used":[51,96],"accurately":[53,98],"measure":[54],"3":[55,84,101,186,193],"6":[58,188,221],"pose":[59,85,103,135,179,189,238],"parameters.":[60,86,104,190],"less":[67],"DOFs":[70],"that":[71,181,200],"produce":[72],"out-of-plane":[73,102],"motion":[74],"so":[76],"it":[77],"enables":[78,227],"only":[79],"rough":[80],"measurement":[81],"these":[83],"matching,":[89],"which":[90,162],"employs":[91,163],"range":[92,165,198],"data,":[93],"determine":[99],"However,":[105],"recognize":[107],"specific":[108,138,207],"3d":[109],"points,":[110],"one":[111],"must":[112],"typically":[113],"make":[114],"strong":[115],"assumptions":[116],"about":[117],"types":[119,139],"features":[121,141,208],"present":[122],"on":[123],"an":[124],"surface.":[126],"Our":[127],"goal":[128],"solve":[131],"more":[133],"general":[134],"problem,":[136],"where":[137],"cannot":[142],"relied":[144],"upon":[145],"because":[146],"they":[147],"might":[148],"not":[149,202],"present.":[151],"This":[152,211],"paper":[153],"first":[154],"introduces":[155],"novel":[157],"approach":[158,212],"binary":[164],"maps":[166],"statistically":[168],"generated":[169],"templates.":[170],"It":[171],"then":[172],"describes":[173],"hybrid":[175],"method":[176],"template-based":[178],"leverages":[182],"remaining":[192],"parameters":[194],"determined":[196],"using":[197,236],"measurements":[199],"do":[201],"require":[203],"presence":[205],"or":[209],"artifacts.":[210],"provides":[213],"high":[215],"degree":[216],"precision":[218],"all":[220],"DOFs,":[222],"yet":[223],"its":[224],"computational":[225],"efficiency":[226],"real-time":[228],"performance.":[229],"Results":[230],"from":[231],"dexterous":[232],"robot":[233],"(Robonaut)":[234],"experiments,":[235],"algorithm,":[239],"discussed.":[241]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}