{"id":"https://openalex.org/W2082098299","doi":"https://doi.org/10.1109/iccvw.2011.6130376","title":"Humanising GrabCut: Learning to segment humans using the Kinect","display_name":"Humanising GrabCut: Learning to segment humans using the Kinect","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2082098299","doi":"https://doi.org/10.1109/iccvw.2011.6130376","mag":"2082098299"},"language":"en","primary_location":{"id":"doi:10.1109/iccvw.2011.6130376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2011.6130376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)","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/A5036282361","display_name":"Varun Gulshan","orcid":null},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Varun Gulshan","raw_affiliation_strings":["Department of Engineering Science, University of Oxford, UK","Dept of Engineering Science, University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"Dept of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083458209","display_name":"Victor Lempitsky","orcid":"https://orcid.org/0000-0003-4118-710X"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Victor Lempitsky","raw_affiliation_strings":["Department of Engineering Science, University of Oxford, UK","Dept of Engineering Science, University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"Dept of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057678172","display_name":"Andrew Zisserman","orcid":"https://orcid.org/0000-0002-8945-8573"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andrew Zisserman","raw_affiliation_strings":["Department of Engineering Science, University of Oxford, UK","Dept of Engineering Science, University of Oxford, UK"],"affiliations":[{"raw_affiliation_string":"Department of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"Dept of Engineering Science, University of Oxford, UK","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036282361"],"corresponding_institution_ids":["https://openalex.org/I40120149"],"apc_list":null,"apc_paid":null,"fwci":4.447,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.95509464,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1127","last_page":"1133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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":0.9995999932289124,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9950000047683716,"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/T12290","display_name":"Human Motion and Animation","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.6431169509887695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6192630529403687},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.548199474811554},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.32791438698768616}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6431169509887695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6192630529403687},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.548199474811554},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.32791438698768616}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/iccvw.2011.6130376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2011.6130376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.644.6416","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.644.6416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://eprints.pascal-network.org/archive/00008424/01/gulshan11.pdf","raw_type":"text"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:0f0cb72e-ddd1-4e46-bd0f-b5dc20de2423","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symplectic Elements","raw_type":"Conference item"},{"id":"pmh:oai:ora.ox.ac.uk:uuid:d4051bba-db8c-44d2-bbfa-05663c928f8c","is_oa":false,"landing_page_url":"https://ora.ox.ac.uk/objects/uuid:d4051bba-db8c-44d2-bbfa-05663c928f8c","pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symplectic Elements at Oxford","raw_type":"Conference"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6399999856948853}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1520005879","https://openalex.org/W1541388462","https://openalex.org/W1548595933","https://openalex.org/W1590899626","https://openalex.org/W1975862670","https://openalex.org/W2005876975","https://openalex.org/W2027480687","https://openalex.org/W2099266834","https://openalex.org/W2113137767","https://openalex.org/W2118585731","https://openalex.org/W2123503110","https://openalex.org/W2124351162","https://openalex.org/W2135512949","https://openalex.org/W2142623206","https://openalex.org/W2154791445","https://openalex.org/W2161969291","https://openalex.org/W2168356304","https://openalex.org/W2186094539","https://openalex.org/W2296770417","https://openalex.org/W2535410496","https://openalex.org/W2535516436","https://openalex.org/W4251485470","https://openalex.org/W6631356444","https://openalex.org/W6632348356","https://openalex.org/W6632941408","https://openalex.org/W6635212758","https://openalex.org/W6677656871","https://openalex.org/W6682519532","https://openalex.org/W6684705394","https://openalex.org/W6728619547"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,139],"Kinect":[1],"provides":[2],"an":[3],"opportunity":[4],"to":[5,24,63,98,113],"collect":[6],"large":[7,43,70],"quantities":[8],"of":[9,45,72,118,146,187],"training":[10],"data":[11],"for":[12],"visual":[13],"learning":[14,23,92],"algorithms":[15],"relatively":[16],"effortlessly.":[17],"To":[18],"this":[19,39],"end":[20],"we":[21],"investigate":[22],"automatically":[25,78],"segment":[26],"humans":[27,49,75,86,147,171],"from":[28,102,129],"cluttered":[29,149],"images":[30,46,145],"(without":[31],"depth":[32],"information)":[33],"given":[34,172],"a":[35,42,69,91,115,134,152,178,184],"bounding":[36,179],"box.":[37],"For":[38],"algorithm,":[40],"obtaining":[41],"dataset":[44,71],"with":[47,94,183],"segmented":[48],"is":[50,87,122,141],"crucial":[51],"as":[52,90],"it":[53],"enables":[54],"the":[55,83,119,163,174,188],"possible":[56],"variations":[57],"in":[58,133,148],"human":[59,120],"appearances":[60],"and":[61,151,181],"backgrounds":[62],"be":[64,77,166],"learnt.":[65],"We":[66,159],"show":[67,161],"that":[68,162],"roughly":[73],"3400":[74],"can":[76,165],"acquired":[79],"very":[80],"cheaply":[81],"using":[82,125],"Kinect.":[84],"Segmenting":[85],"then":[88,123],"cast":[89],"problem":[93],"linear":[95],"classifiers":[96,109],"trained":[97],"predict":[99],"segmentation":[100,117],"masks":[101],"sparsely":[103],"coded":[104],"local":[105,130],"HOG":[106],"descriptors.":[107],"These":[108],"introduce":[110],"top-down":[111],"knowledge":[112],"obtain":[114],"crude":[116],"which":[121],"refined":[124],"bottom":[126],"up":[127],"information":[128],"color":[131],"models":[132],"Snap-Cut":[135],"[2]":[136],"like":[137],"fashion.":[138],"method":[140,164],"quantitatively":[142],"evaluated":[143],"on":[144],"scenes,":[150],"high":[153],"performance":[154],"obtained":[155],"(88:5%":[156],"overlap":[157],"score).":[158],"also":[160],"completely":[167],"automated":[168],"-":[169],"segmenting":[170],"only":[173],"images,":[175],"without":[176],"requiring":[177],"box,":[180],"compare":[182],"previous":[185],"state":[186],"art":[189],"method.":[190]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
