{"id":"https://openalex.org/W3135468597","doi":"https://doi.org/10.1142/s0219467821500418","title":"Curve and Surface Fitting Techniques in Computer Vision","display_name":"Curve and Surface Fitting Techniques in Computer Vision","publication_year":2021,"publication_date":"2021-03-08","ids":{"openalex":"https://openalex.org/W3135468597","doi":"https://doi.org/10.1142/s0219467821500418","mag":"3135468597"},"language":"en","primary_location":{"id":"doi:10.1142/s0219467821500418","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467821500418","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-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/A5109136341","display_name":"Kyle Brown","orcid":"https://orcid.org/0000-0003-0629-8285"},"institutions":[{"id":"https://openalex.org/I19648265","display_name":"Wright State University","ror":"https://ror.org/04qk6pt94","country_code":"US","type":"education","lineage":["https://openalex.org/I19648265"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Brown","raw_affiliation_strings":["Department of Computer Science, Wright State University, 3640 Colonel Glenn Highway, Dayton, Ohio 45435, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Wright State University, 3640 Colonel Glenn Highway, Dayton, Ohio 45435, USA","institution_ids":["https://openalex.org/I19648265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025446324","display_name":"Nikolaos Bourbakis","orcid":"https://orcid.org/0000-0003-1507-614X"},"institutions":[{"id":"https://openalex.org/I19648265","display_name":"Wright State University","ror":"https://ror.org/04qk6pt94","country_code":"US","type":"education","lineage":["https://openalex.org/I19648265"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nikolaos Bourbakis","raw_affiliation_strings":["CART Center, Wright State University, 3640 Colonel Glenn Highway, Dayton, Ohio 45435, USA"],"affiliations":[{"raw_affiliation_string":"CART Center, Wright State University, 3640 Colonel Glenn Highway, Dayton, Ohio 45435, USA","institution_ids":["https://openalex.org/I19648265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025446324"],"corresponding_institution_ids":["https://openalex.org/I19648265"],"apc_list":null,"apc_paid":null,"fwci":0.1921,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4576634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"21","issue":"04","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","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/T12549","display_name":"Image and Object Detection Techniques","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/T10531","display_name":"Advanced Vision and Imaging","score":0.9973000288009644,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9969000220298767,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.720456600189209},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6651244759559631},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6345601081848145},{"id":"https://openalex.org/keywords/curve-fitting","display_name":"Curve fitting","score":0.5927383899688721},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5274553298950195},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5221838355064392},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.4732906222343445},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40982455015182495},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3672651946544647},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35937798023223877},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3233298063278198},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29021570086479187},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18074986338615417},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.06898307800292969}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.720456600189209},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6651244759559631},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6345601081848145},{"id":"https://openalex.org/C184389593","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Curve fitting","level":2,"score":0.5927383899688721},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5274553298950195},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5221838355064392},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.4732906222343445},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40982455015182495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3672651946544647},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35937798023223877},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3233298063278198},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29021570086479187},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18074986338615417},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.06898307800292969},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219467821500418","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467821500418","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W86299341","https://openalex.org/W206745480","https://openalex.org/W1915668717","https://openalex.org/W1981115560","https://openalex.org/W2009086487","https://openalex.org/W2014296749","https://openalex.org/W2038233234","https://openalex.org/W2049659999","https://openalex.org/W2054585288","https://openalex.org/W2056402339","https://openalex.org/W2068400867","https://openalex.org/W2083527020","https://openalex.org/W2135370022","https://openalex.org/W2138001711","https://openalex.org/W2146656095","https://openalex.org/W2162870748","https://openalex.org/W2167623131","https://openalex.org/W2193045528","https://openalex.org/W2264065105","https://openalex.org/W2404806423","https://openalex.org/W2587938668","https://openalex.org/W2600649561","https://openalex.org/W2963598138"],"related_works":["https://openalex.org/W2012531322","https://openalex.org/W2785900585","https://openalex.org/W2353730437","https://openalex.org/W2490303674","https://openalex.org/W2609066826","https://openalex.org/W2810752900","https://openalex.org/W3186538219","https://openalex.org/W2065843430","https://openalex.org/W2358981651","https://openalex.org/W2160477533"],"abstract_inverted_index":{"Curve":[0],"and":[1,33,91,116],"surface-fitting":[2],"are":[3,18,85],"classic":[4],"problems":[5],"of":[6,52,67,88,98,102,113,118],"approximation":[7,39],"that":[8],"find":[9],"use":[10,66],"in":[11,61],"many":[12],"fields,":[13],"including":[14],"computer":[15,62],"vision.":[16,63],"There":[17],"two":[19],"broad":[20,100],"approaches":[21],"to":[22,29,44,86,105],"the":[23,75,89,99,103,114,119],"problem":[24],"\u2014":[25],"interpolation,":[26],"which":[27,35,40,73],"seeks":[28,36],"fit":[30],"points":[31],"exactly,":[32],"regression,":[34],"a":[37,56,95,110],"rougher":[38],"is":[41],"more":[42],"robust":[43],"noise.":[45],"This":[46,93],"survey":[47],"looks":[48],"at":[49],"several":[50,126],"techniques":[51,76],"both":[53],"kinds,":[54],"with":[55],"particular":[57],"focus":[58],"on":[59,77,81,125],"applications":[60],"We":[64],"make":[65],"an":[68],"empirical":[69],"first-level":[70],"evaluation":[71,112],"approach":[72],"scores":[74],"multiple":[78],"features":[79],"based":[80],"how":[82],"important":[83],"they":[84],"users":[87],"technique":[90,104,120],"developers.":[92],"provides":[94],"quick":[96],"summary":[97],"applicability":[101],"most":[106],"situations,":[107],"rather":[108],"than":[109],"deep":[111],"performance":[115],"accuracy":[117],"obtained":[121],"by":[122],"running":[123],"it":[124],"datasets.":[127]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}