{"id":"https://openalex.org/W2168572916","doi":"https://doi.org/10.1109/fg.2013.6553733","title":"Fast propagation-based skin regions segmentation in color images","display_name":"Fast propagation-based skin regions segmentation in color images","publication_year":2013,"publication_date":"2013-04-01","ids":{"openalex":"https://openalex.org/W2168572916","doi":"https://doi.org/10.1109/fg.2013.6553733","mag":"2168572916"},"language":"en","primary_location":{"id":"doi:10.1109/fg.2013.6553733","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2013.6553733","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)","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/A5086221093","display_name":"Micha\u0142 Kawulok","orcid":"https://orcid.org/0000-0002-3669-5110"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Michal Kawulok","raw_affiliation_strings":["Institute of Informatics, Silesian University of Technology, Gliwice, Poland"],"affiliations":[{"raw_affiliation_string":"Institute of Informatics, Silesian University of Technology, Gliwice, Poland","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5086221093"],"corresponding_institution_ids":["https://openalex.org/I119004910"],"apc_list":null,"apc_paid":null,"fwci":8.6087,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.98121153,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958999752998352,"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/T10057","display_name":"Face and Expression Recognition","score":0.9890000224113464,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8165285587310791},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7031540870666504},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6743393540382385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.650456428527832},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5912782549858093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5666511654853821},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5286398530006409},{"id":"https://openalex.org/keywords/hue","display_name":"Hue","score":0.5189292430877686},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.4674462080001831}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8165285587310791},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7031540870666504},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6743393540382385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.650456428527832},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5912782549858093},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5666511654853821},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5286398530006409},{"id":"https://openalex.org/C126537357","wikidata":"https://www.wikidata.org/wiki/Q372948","display_name":"Hue","level":2,"score":0.5189292430877686},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.4674462080001831}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fg.2013.6553733","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2013.6553733","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)","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":42,"referenced_works":["https://openalex.org/W1514121328","https://openalex.org/W1554950011","https://openalex.org/W1565294508","https://openalex.org/W1585252135","https://openalex.org/W1822537810","https://openalex.org/W1852312282","https://openalex.org/W1963810131","https://openalex.org/W1972065656","https://openalex.org/W1986371005","https://openalex.org/W2006676870","https://openalex.org/W2016557874","https://openalex.org/W2063965450","https://openalex.org/W2078088780","https://openalex.org/W2083530817","https://openalex.org/W2091313930","https://openalex.org/W2099027612","https://openalex.org/W2100648635","https://openalex.org/W2106075360","https://openalex.org/W2106309274","https://openalex.org/W2110159536","https://openalex.org/W2114724217","https://openalex.org/W2124862611","https://openalex.org/W2130102890","https://openalex.org/W2130462770","https://openalex.org/W2136900990","https://openalex.org/W2137940226","https://openalex.org/W2152633621","https://openalex.org/W2153746365","https://openalex.org/W2161236525","https://openalex.org/W2163768323","https://openalex.org/W2168895155","https://openalex.org/W2886440561","https://openalex.org/W2952793010","https://openalex.org/W3149066084","https://openalex.org/W6630652119","https://openalex.org/W6633520255","https://openalex.org/W6633820770","https://openalex.org/W6635179879","https://openalex.org/W6680428043","https://openalex.org/W6682738433","https://openalex.org/W6683607639","https://openalex.org/W6753460930"],"related_works":["https://openalex.org/W4320518079","https://openalex.org/W2039822179","https://openalex.org/W4386771591","https://openalex.org/W1990245967","https://openalex.org/W2054177013","https://openalex.org/W2972873516","https://openalex.org/W2022832287","https://openalex.org/W2121052767","https://openalex.org/W2952164672","https://openalex.org/W1522196789"],"abstract_inverted_index":{"This":[0],"paper":[1,115],"introduces":[2],"a":[3,25,104],"new":[4],"method":[5,123,150],"for":[6,96],"skin":[7,16,34,48,65,77,111,126],"regions":[8],"segmentation":[9],"which":[10,29,142],"consists":[11],"in":[12,91,103],"spatial":[13,74,131],"analysis":[14,75],"of":[15,27,33,63,76,107,120,137,147],"probability":[17,49],"maps":[18],"obtained":[19],"using":[20,92],"pixel-wise":[21],"detectors.":[22],"There":[23],"are":[24],"number":[26],"methods":[28],"use":[30],"various":[31],"techniques":[32],"color":[35,45],"modeling":[36],"to":[37,57,154],"classify":[38],"every":[39],"individual":[40],"pixel":[41],"or":[42],"transform":[43,95],"input":[44],"images":[46],"into":[47],"maps,":[50],"but":[51],"their":[52],"performance":[53],"is":[54],"limited":[55],"due":[56],"high":[58,145],"variance":[59],"and":[60,110,151],"low":[61],"specificity":[62],"the":[64,93,98,101,114,121,148],"color.":[66],"Detection":[67],"precision":[68],"can":[69],"be":[70],"enhanced":[71],"based":[72],"on":[73],"pixels,":[78],"however":[79],"this":[80],"direction":[81],"has":[82],"been":[83],"little":[84],"explored":[85],"so":[86],"far.":[87],"Our":[88],"contribution":[89],"lies":[90],"distance":[94],"propagating":[97],"\u201cskinness\u201d":[99],"across":[100],"image":[102],"combined":[105],"domain":[106],"luminance,":[108],"hue":[109],"probability.":[112],"In":[113],"we":[116,134],"explain":[117],"theoretical":[118],"advantages":[119],"proposed":[122,149],"over":[124],"alternative":[125],"detectors":[127],"that":[128],"also":[129],"perform":[130],"analysis.":[132],"Finally,":[133],"present":[135],"results":[136],"an":[138],"extensive":[139],"experimental":[140],"study":[141],"clearly":[143],"indicate":[144],"competitiveness":[146],"its":[152],"relevance":[153],"gesture":[155],"recognition.":[156]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
