{"id":"https://openalex.org/W2048557206","doi":"https://doi.org/10.1109/cvpr.2012.6247796","title":"Fast axis estimation from a segment of rotationally symmetric object","display_name":"Fast axis estimation from a segment of rotationally symmetric object","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2048557206","doi":"https://doi.org/10.1109/cvpr.2012.6247796","mag":"2048557206"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6247796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/A5102809360","display_name":"Dongjin Han","orcid":"https://orcid.org/0000-0003-1093-1741"},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dongjin Han","raw_affiliation_strings":["ITRC, Soongsil University, Seoul, South Korea","ITRC, Soongsil Univ., Seoul, Korea#TAB#"],"affiliations":[{"raw_affiliation_string":"ITRC, Soongsil University, Seoul, South Korea","institution_ids":["https://openalex.org/I141371507"]},{"raw_affiliation_string":"ITRC, Soongsil Univ., Seoul, Korea#TAB#","institution_ids":["https://openalex.org/I141371507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101891059","display_name":"David B. Cooper","orcid":"https://orcid.org/0000-0002-4225-5242"},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. B. Cooper","raw_affiliation_strings":["Lems, Brown University, Providence, RI, USA","LEMS, Brown Univ., Providence, RI"],"affiliations":[{"raw_affiliation_string":"Lems, Brown University, Providence, RI, USA","institution_ids":["https://openalex.org/I27804330"]},{"raw_affiliation_string":"LEMS, Brown Univ., Providence, RI","institution_ids":["https://openalex.org/I27804330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102095825","display_name":"Hernsoo Hahn","orcid":null},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hern-soo Hahn","raw_affiliation_strings":["E.E., Soongsil University, Seoul, South Korea","E.E., Soongsil Univ., Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"E.E., Soongsil University, Seoul, South Korea","institution_ids":["https://openalex.org/I141371507"]},{"raw_affiliation_string":"E.E., Soongsil Univ., Seoul, Korea","institution_ids":["https://openalex.org/I141371507"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102809360"],"corresponding_institution_ids":["https://openalex.org/I141371507"],"apc_list":null,"apc_paid":null,"fwci":0.8236,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.74922475,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"681","issue":null,"first_page":"1154","last_page":"1161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":1.0,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":1.0,"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":0.9987000226974487,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.6687716841697693},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5248354077339172},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48175859451293945},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47800934314727783},{"id":"https://openalex.org/keywords/principal-axis-theorem","display_name":"Principal axis theorem","score":0.4780029356479645},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.47757866978645325},{"id":"https://openalex.org/keywords/principal-curvature","display_name":"Principal curvature","score":0.4412723183631897},{"id":"https://openalex.org/keywords/circumference","display_name":"Circumference","score":0.4193267822265625},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.41099750995635986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38253626227378845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37873348593711853},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.33647453784942627},{"id":"https://openalex.org/keywords/mean-curvature","display_name":"Mean curvature","score":0.249782532453537},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.11843475699424744},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10663840174674988}],"concepts":[{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.6687716841697693},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5248354077339172},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48175859451293945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47800934314727783},{"id":"https://openalex.org/C161326058","wikidata":"https://www.wikidata.org/wiki/Q7245073","display_name":"Principal axis theorem","level":2,"score":0.4780029356479645},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.47757866978645325},{"id":"https://openalex.org/C16977076","wikidata":"https://www.wikidata.org/wiki/Q1589551","display_name":"Principal curvature","level":4,"score":0.4412723183631897},{"id":"https://openalex.org/C166504685","wikidata":"https://www.wikidata.org/wiki/Q843905","display_name":"Circumference","level":2,"score":0.4193267822265625},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41099750995635986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38253626227378845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37873348593711853},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.33647453784942627},{"id":"https://openalex.org/C175017881","wikidata":"https://www.wikidata.org/wiki/Q1318998","display_name":"Mean curvature","level":3,"score":0.249782532453537},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.11843475699424744},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10663840174674988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2012.6247796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6247796","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","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/W15949264","https://openalex.org/W123897999","https://openalex.org/W1587851221","https://openalex.org/W1978023112","https://openalex.org/W1985494771","https://openalex.org/W1990542071","https://openalex.org/W2093161589","https://openalex.org/W2104776149","https://openalex.org/W2120599803","https://openalex.org/W2134905288","https://openalex.org/W2150570021","https://openalex.org/W2170877358","https://openalex.org/W6675738515"],"related_works":["https://openalex.org/W2039089021","https://openalex.org/W2130450339","https://openalex.org/W2950620193","https://openalex.org/W2354710386","https://openalex.org/W2005204240","https://openalex.org/W2909819188","https://openalex.org/W2021032139","https://openalex.org/W2350692777","https://openalex.org/W2175710703","https://openalex.org/W2963067241"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,12,37,52,55,98,132,144],"new":[4],"method":[5,65],"for":[6,151,183],"estimating":[7],"the":[8,22,28,63,83,86,93,106,115,140,170,177,193],"symmetric":[9,84],"axis":[10,29,46,68,152],"of":[11,25,54,138,143,160,185,189],"pottery":[13,145,201],"from":[14],"its":[15],"small":[16],"fragment":[17,38],"using":[18,71,155],"surface":[19],"geometry.":[20],"For":[21],"automatic":[23],"assembly":[24],"broken":[26],"sherds,":[27],"estimation":[30,69],"is":[31,39,42,77,95,108,131,136,153],"an":[32],"important":[33],"measure":[34],"[2].":[35],"When":[36],"small,":[40],"it":[41,49],"difficult":[43],"to":[44],"estimate":[45,82],"orientation":[47],"since":[48],"looks":[50],"like":[51],"patch":[53],"sphere":[56],"and":[57,164],"conventional":[58],"methods":[59],"mostly":[60],"fail,":[61],"but":[62],"proposed":[64,87],"provides":[66],"reliable":[67],"by":[70,196],"multiple":[72],"constraints.":[73],"The":[74,158,187],"computational":[75],"cost":[76],"also":[78,114,174],"much":[79],"lowered.":[80],"To":[81],"axis,":[85],"algorithm":[88],"uses":[89],"three":[90],"constraints:":[91],"(1)":[92],"curvature":[94,107,163],"constant":[96],"on":[97,121],"circumference":[99],"C":[100,122,127],"<sub":[101,123,128],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[102,124,129],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">H</sub>":[103,125,130],".":[104,126],"(2)":[105],"invariant":[109],"in":[110,169,200],"any":[111],"scale.":[112],"(3)":[113],"principal":[116,165,178],"curvatures":[117,166,179],"does":[118],"not":[119],"vary":[120],"planar":[133],"circle":[134],"which":[135],"one":[137],"all":[139],"possible":[141],"circumferences":[142],"or":[146],"sherd.":[147],"A":[148],"hypothesis":[149],"test":[150],"performed":[154],"maximum":[156],"likelihood.":[157],"variance":[159],"curvature,":[161],"multi-scale":[162],"are":[167],"computed":[168],"likelihood":[171],"function.":[172],"We":[173],"show":[175],"that":[176],"can":[180],"be":[181],"used":[182],"grouping":[184,188],"sherds.":[186],"sherds":[190],"will":[191],"reduce":[192],"computation":[194],"significantly":[195],"omitting":[197],"impossible":[198],"configurations":[199],"assembly.":[202]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
