{"id":"https://openalex.org/W2027786113","doi":"https://doi.org/10.1109/icce.2014.6775931","title":"Human segmentation based on GrabCut in real-time video sequences","display_name":"Human segmentation based on GrabCut in real-time video sequences","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2027786113","doi":"https://doi.org/10.1109/icce.2014.6775931","mag":"2027786113"},"language":"en","primary_location":{"id":"doi:10.1109/icce.2014.6775931","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce.2014.6775931","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100381589","display_name":"Sohee Park","orcid":"https://orcid.org/0000-0003-4833-6016"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sohee Park","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (ETRI), Daejeon, S. Korea","Electron. & Telecommun. Res. Inst. (ETRI), Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (ETRI), Daejeon, S. Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Electron. & Telecommun. Res. Inst. (ETRI), Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101596480","display_name":"Jang\u2010Hee Yoo","orcid":"https://orcid.org/0000-0003-0495-9211"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jang-Hee Yoo","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (ETRI), Daejeon, S. Korea","Electron. & Telecommun. Res. Inst. (ETRI), Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (ETRI), Daejeon, S. Korea","institution_ids":["https://openalex.org/I142401562"]},{"raw_affiliation_string":"Electron. & Telecommun. Res. Inst. (ETRI), Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":0.1798,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.43133827,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991999864578247,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9969000220298767,"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":0.9936000108718872,"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/background-subtraction","display_name":"Background subtraction","score":0.9066003561019897},{"id":"https://openalex.org/keywords/silhouette","display_name":"Silhouette","score":0.8649574518203735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7865605354309082},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7564165592193604},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7240146994590759},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7093365788459778},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6067053079605103},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.594327986240387},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4338891804218292},{"id":"https://openalex.org/keywords/subtraction","display_name":"Subtraction","score":0.42737269401550293},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.32072344422340393},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2616504728794098}],"concepts":[{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.9066003561019897},{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.8649574518203735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7865605354309082},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7564165592193604},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7240146994590759},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7093365788459778},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6067053079605103},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.594327986240387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4338891804218292},{"id":"https://openalex.org/C68060419","wikidata":"https://www.wikidata.org/wiki/Q40754","display_name":"Subtraction","level":2,"score":0.42737269401550293},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.32072344422340393},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2616504728794098},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce.2014.6775931","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce.2014.6775931","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2108314533","https://openalex.org/W2123701509","https://openalex.org/W2124351162","https://openalex.org/W2138948290","https://openalex.org/W2537213512","https://openalex.org/W6728672063"],"related_works":["https://openalex.org/W1622964048","https://openalex.org/W30315714","https://openalex.org/W1906975550","https://openalex.org/W1965274140","https://openalex.org/W28439884","https://openalex.org/W3161582060","https://openalex.org/W2112497652","https://openalex.org/W2104051139","https://openalex.org/W2189228877","https://openalex.org/W3100796443"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,20],"present":[4],"a":[5],"fully-automatic":[6],"human":[7,17,25,36,47,53,85],"segmentation":[8],"method":[9,31,82,102],"without":[10,94],"iteration":[11],"in":[12,46,91,110],"video":[13,92,112],"sequences.":[14,113],"To":[15],"segment":[16,84],"body":[18],"accurately,":[19],"adopt":[21],"coarse-to-fine":[22],"approach":[23],"using":[24],"detection":[26],"and":[27,49,58,74],"background":[28,75],"subtraction.":[29],"HoG-based":[30],"is":[32,40],"used":[33,41],"to":[34,42,77,89],"detect":[35],"ROI.":[37],"Background":[38],"subtraction":[39],"subtract":[43],"subject":[44,56],"image":[45,61],"ROI":[48],"skeleton":[50,60],"image.":[51],"The":[52,67],"ROI,":[54],"the":[55,59,80,100],"image,":[57],"are":[62],"initialization":[63,68],"values":[64,69],"of":[65],"GrabCut.":[66,78],"provide":[70],"more":[71],"accurate":[72],"foreground":[73],"information":[76],"Therefore":[79],"proposed":[81,101],"can":[83,103],"silhouette":[86],"accurately":[87],"enough":[88],"apply":[90],"analysis":[93],"iteration.":[95],"Experimental":[96],"results":[97],"show":[98],"that":[99],"be":[104],"achieved":[105],"better":[106],"performance":[107],"than":[108],"GrabCut":[109],"real-time":[111]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}