{"id":"https://openalex.org/W2294169006","doi":"https://doi.org/10.5220/0005338906300637","title":"Curvature-based Human Body Parts Segmentation in Physiotherapy","display_name":"Curvature-based Human Body Parts Segmentation in Physiotherapy","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2294169006","doi":"https://doi.org/10.5220/0005338906300637","mag":"2294169006"},"language":"en","primary_location":{"id":"doi:10.5220/0005338906300637","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005338906300637","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0005338906300637","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017842431","display_name":"Francis Deboeverie","orcid":null},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Francis Deboeverie","raw_affiliation_strings":["UGent/iMinds, Belgium"],"affiliations":[{"raw_affiliation_string":"UGent/iMinds, Belgium","institution_ids":["https://openalex.org/I39327780","https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071550534","display_name":"Roeland De Geest","orcid":"https://orcid.org/0000-0003-4897-7921"},"institutions":[{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]},{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Roeland De Geest","raw_affiliation_strings":["KU Leuven/iMinds, Belgium"],"affiliations":[{"raw_affiliation_string":"KU Leuven/iMinds, Belgium","institution_ids":["https://openalex.org/I39327780","https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074816094","display_name":"Tinne Tuytelaars","orcid":"https://orcid.org/0000-0003-3307-9723"},"institutions":[{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]},{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Tinne Tuytelaars","raw_affiliation_strings":["KU Leuven/iMinds, Belgium"],"affiliations":[{"raw_affiliation_string":"KU Leuven/iMinds, Belgium","institution_ids":["https://openalex.org/I39327780","https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068050252","display_name":"Peter Veelaert","orcid":"https://orcid.org/0000-0003-4746-9087"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Peter Veelaert","raw_affiliation_strings":["UGent/iMinds, Belgium"],"affiliations":[{"raw_affiliation_string":"UGent/iMinds, Belgium","institution_ids":["https://openalex.org/I39327780","https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071483672","display_name":"Wilfried Philips","orcid":"https://orcid.org/0000-0003-4456-4353"},"institutions":[{"id":"https://openalex.org/I39327780","display_name":"iMinds","ror":"https://ror.org/03baec336","country_code":"BE","type":"nonprofit","lineage":["https://openalex.org/I39327780"]},{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Wilfried Philips","raw_affiliation_strings":["UGent/iMinds, Belgium"],"affiliations":[{"raw_affiliation_string":"UGent/iMinds, Belgium","institution_ids":["https://openalex.org/I39327780","https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5017842431"],"corresponding_institution_ids":["https://openalex.org/I32597200","https://openalex.org/I39327780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.15551614,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"630","last_page":"637"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","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/T10036","display_name":"Advanced Neural Network Applications","score":0.9915000200271606,"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/torso","display_name":"Torso","score":0.8225226402282715},{"id":"https://openalex.org/keywords/human-body","display_name":"Human body","score":0.7799285650253296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7629542946815491},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7520673274993896},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7418152093887329},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.6355485320091248},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.626617431640625},{"id":"https://openalex.org/keywords/human-body-model","display_name":"Human-body model","score":0.4793458878993988},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4783758223056793},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.44524165987968445},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.41190996766090393},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.354436993598938},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28210076689720154},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23960813879966736},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.20984750986099243},{"id":"https://openalex.org/keywords/anatomy","display_name":"Anatomy","score":0.1194063127040863}],"concepts":[{"id":"https://openalex.org/C523889960","wikidata":"https://www.wikidata.org/wiki/Q160695","display_name":"Torso","level":2,"score":0.8225226402282715},{"id":"https://openalex.org/C193293595","wikidata":"https://www.wikidata.org/wiki/Q23852","display_name":"Human body","level":2,"score":0.7799285650253296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7629542946815491},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7520673274993896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7418152093887329},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.6355485320091248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.626617431640625},{"id":"https://openalex.org/C2781089380","wikidata":"https://www.wikidata.org/wiki/Q5936753","display_name":"Human-body model","level":2,"score":0.4793458878993988},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4783758223056793},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.44524165987968445},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.41190996766090393},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.354436993598938},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28210076689720154},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23960813879966736},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.20984750986099243},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.1194063127040863},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.5220/0005338906300637","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005338906300637","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/511304","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/511304","pdf_url":null,"source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"International conference on computer vision theory and applications - VISAPP 2015, Berlin, Germany, 11-14 March 2015","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:archive.ugent.be:5902749","is_oa":false,"landing_page_url":"http://hdl.handle.net/1854/LU-5902749","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9789897580895","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.5220/0005338906300637","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005338906300637","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Computer Vision Theory and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1983705368","https://openalex.org/W1990909622","https://openalex.org/W1993991024","https://openalex.org/W2000586821","https://openalex.org/W2008840450","https://openalex.org/W2018793343","https://openalex.org/W2020227869","https://openalex.org/W2020715422","https://openalex.org/W2023156108","https://openalex.org/W2032481801","https://openalex.org/W2042322506","https://openalex.org/W2056426432","https://openalex.org/W2067191022","https://openalex.org/W2095999100","https://openalex.org/W2097514097","https://openalex.org/W2098291217","https://openalex.org/W2103621314","https://openalex.org/W2105245249","https://openalex.org/W2110164620","https://openalex.org/W2119102184","https://openalex.org/W2121499649","https://openalex.org/W2121947440","https://openalex.org/W2124217265","https://openalex.org/W2124260943","https://openalex.org/W2142961844","https://openalex.org/W2150464734","https://openalex.org/W2158866619","https://openalex.org/W2162253476","https://openalex.org/W2167239433","https://openalex.org/W2304523937"],"related_works":["https://openalex.org/W2391783724","https://openalex.org/W2522411600","https://openalex.org/W3148835666","https://openalex.org/W2013629294","https://openalex.org/W2292055224","https://openalex.org/W1981183068","https://openalex.org/W2939306628","https://openalex.org/W2070248107","https://openalex.org/W1911419961","https://openalex.org/W2367990508"],"abstract_inverted_index":{"Analysing":[0],"human":[1,12,30,37,65,84,88,101,111,134],"sports":[2],"activity":[3],"in":[4,60],"computer":[5],"vision":[6],"requires":[7],"reliable":[8],"segmentation":[9,90],"of":[10,36,74,78,133],"the":[11,57,76,83,123],"body":[13,31,66,85,89,102,112,135],"into":[14,41],"meaningful":[15],"parts,":[16],"such":[17],"as":[18],"arms,":[19],"torso":[20],"and":[21,104,121,130],"legs.":[22],"Therefore,":[23],"we":[24],"present":[25],"a":[26,95],"novel":[27],"strategy":[28],"for":[29],"segmentation.":[32],"Firstly,":[33],"greyscale":[34],"images":[35],"bodies":[38],"are":[39,68],"divided":[40],"smooth":[42],"intensity":[43],"patches":[44],"with":[45,94,110],"an":[46],"adaptive":[47],"region":[48],"growing":[49],"algorithm":[50],"based":[51,115],"on":[52,116],"low-degree":[53],"polynomial":[54],"fitting.":[55],"Then,":[56],"key":[58],"idea":[59],"this":[61],"paper":[62],"is":[63,91],"that":[64],"parts":[67,113],"approximated":[69],"by":[70],"nearly":[71],"cylindrical":[72],"surfaces,":[73],"which":[75],"axes":[77],"minimum":[79],"curvature":[80],"accurately":[81],"reconstruct":[82],"skeleton.":[86],"Next,":[87],"qualitatively":[92],"evaluated":[93],"line":[96],"segment":[97],"distance":[98],"between":[99],"reconstructed":[100],"skeletons":[103],"ground":[105],"truth":[106],"skeletons.":[107,136],"When":[108],"compared":[109],"segmentations":[114,129],"mean":[117],"shift,":[118],"normalized":[119],"cuts":[120],"watersheds,":[122],"proposed":[124],"method":[125],"achieves":[126],"more":[127],"accurate":[128],"better":[131],"reconstructions":[132]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}