{"id":"https://openalex.org/W2821320768","doi":"https://doi.org/10.1109/ivcnz.2017.8402510","title":"SIFT localisation accuracy on interpolated speckle images","display_name":"SIFT localisation accuracy on interpolated speckle images","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2821320768","doi":"https://doi.org/10.1109/ivcnz.2017.8402510","mag":"2821320768"},"language":"en","primary_location":{"id":"doi:10.1109/ivcnz.2017.8402510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz.2017.8402510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Image and Vision Computing New Zealand (IVCNZ)","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/A5020284776","display_name":"Victor Wang","orcid":"https://orcid.org/0000-0001-9633-1506"},"institutions":[{"id":"https://openalex.org/I185492890","display_name":"University of Canterbury","ror":"https://ror.org/03y7q9t39","country_code":"NZ","type":"education","lineage":["https://openalex.org/I185492890"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Victor Wang","raw_affiliation_strings":["Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand","institution_ids":["https://openalex.org/I185492890"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048027374","display_name":"Michael Hayes","orcid":"https://orcid.org/0000-0002-6712-9509"},"institutions":[{"id":"https://openalex.org/I185492890","display_name":"University of Canterbury","ror":"https://ror.org/03y7q9t39","country_code":"NZ","type":"education","lineage":["https://openalex.org/I185492890"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Michael Hayes","raw_affiliation_strings":["Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand","institution_ids":["https://openalex.org/I185492890"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.2454259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"406","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9997000098228455,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9984999895095825,"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/oversampling","display_name":"Oversampling","score":0.9160916209220886},{"id":"https://openalex.org/keywords/sinc-function","display_name":"Sinc function","score":0.6782047748565674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6755660772323608},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6382603049278259},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.556581974029541},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5341020822525024},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5296421051025391},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.4930717647075653},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.4792071282863617},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46261197328567505},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4417414367198944},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.42988041043281555},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33900973200798035},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.31178876757621765},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1185426115989685}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.9160916209220886},{"id":"https://openalex.org/C152303783","wikidata":"https://www.wikidata.org/wiki/Q855949","display_name":"Sinc function","level":2,"score":0.6782047748565674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6755660772323608},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6382603049278259},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.556581974029541},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5341020822525024},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5296421051025391},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.4930717647075653},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.4792071282863617},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46261197328567505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4417414367198944},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.42988041043281555},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33900973200798035},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31178876757621765},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1185426115989685},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivcnz.2017.8402510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivcnz.2017.8402510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Image and Vision Computing New Zealand (IVCNZ)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310654","display_name":"Indian National Science Academy","ror":"https://ror.org/051475v86"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W99071287","https://openalex.org/W1516304599","https://openalex.org/W1523306195","https://openalex.org/W1659707536","https://openalex.org/W1677409904","https://openalex.org/W2010610937","https://openalex.org/W2011116888","https://openalex.org/W2012396049","https://openalex.org/W2025887329","https://openalex.org/W2033819227","https://openalex.org/W2042316011","https://openalex.org/W2050406342","https://openalex.org/W2073935280","https://openalex.org/W2116577232","https://openalex.org/W2119605622","https://openalex.org/W2124386111","https://openalex.org/W2151103935","https://openalex.org/W2155712649","https://openalex.org/W2290596958","https://openalex.org/W2564056344","https://openalex.org/W2570085479","https://openalex.org/W3210232381","https://openalex.org/W4205398292","https://openalex.org/W4229520950","https://openalex.org/W6603996231","https://openalex.org/W6653156638","https://openalex.org/W6803376173"],"related_works":["https://openalex.org/W2065648684","https://openalex.org/W2009383287","https://openalex.org/W2042914788","https://openalex.org/W2182190754","https://openalex.org/W4321264664","https://openalex.org/W2055824452","https://openalex.org/W2121688719","https://openalex.org/W2727313114","https://openalex.org/W2016481886","https://openalex.org/W1989852278"],"abstract_inverted_index":{"Although":[0],"sine":[1],"interpolation":[2,25],"is":[3,55,87],"considered":[4],"ideal":[5],"for":[6],"adequately":[7],"sampled":[8],"bandlimited":[9],"data,":[10],"speckle":[11],"images":[12,67],"are":[13,72],"not":[14,56],"always":[15],"well":[16,33],"sampled.":[17],"This":[18],"paper":[19],"explores":[20],"the":[21,35,40,50,75,102,108,114],"relationship":[22],"between":[23,66],"sinc":[24,59],"and":[26,63,82,107],"localisation":[27,64,116],"accuracy":[28],"of":[29,37,42,104,110,118],"SIFT":[30,46],"features,":[31],"as":[32,34],"effect":[36],"oversampling":[38,99],"on":[39],"quality":[41],"feature":[43],"correspondences.":[44],"Since":[45],"detects":[47],"features":[48,106],"in":[49],"Gaussian":[51],"scale":[52],"space,":[53],"it":[54],"concordant":[57],"with":[58,93],"interpolation.":[60],"The":[61],"repeatability":[62],"errors":[65],"shifted":[68],"by":[69],"fractional":[70],"displacements":[71],"demonstrated":[73],"under":[74],"conditions":[76],"of:":[77],"no":[78],"oversampling,":[79,81],"two-times":[80],"four-times":[83,98],"oversampling.":[84],"Feature":[85],"matching":[86],"shown":[88],"to":[89],"be":[90],"largely":[91],"infeasible":[92],"only":[94],"Nyquist":[95],"sampling,":[96],"whereas":[97],"significantly":[100],"increases":[101],"number":[103],"detected":[105],"proportion":[109],"inlier":[111],"matches,":[112],"while":[113],"mean":[115],"error":[117],"these":[119],"matches":[120],"also":[121],"decreases":[122],"more":[123],"than":[124],"four-fold.":[125]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}