{"id":"https://openalex.org/W2575029978","doi":"https://doi.org/10.1109/apsipa.2016.7820823","title":"Depth guided selection of adaptive region of interest for Grabcut-based image segmentation","display_name":"Depth guided selection of adaptive region of interest for Grabcut-based image segmentation","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2575029978","doi":"https://doi.org/10.1109/apsipa.2016.7820823","mag":"2575029978"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2016.7820823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2016.7820823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","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/A5101886657","display_name":"Garam Kim","orcid":"https://orcid.org/0000-0001-6517-7120"},"institutions":[{"id":"https://openalex.org/I48566637","display_name":"Ulsan National Institute of Science and Technology","ror":"https://ror.org/017cjz748","country_code":"KR","type":"education","lineage":["https://openalex.org/I48566637"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Garam Kim","raw_affiliation_strings":["School of Electrical and Computer Engineering, UNIST, Ulsan, Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, UNIST, Ulsan, Korea","institution_ids":["https://openalex.org/I48566637"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073397129","display_name":"Jae-Young Sim","orcid":"https://orcid.org/0000-0003-2636-7444"},"institutions":[{"id":"https://openalex.org/I48566637","display_name":"Ulsan National Institute of Science and Technology","ror":"https://ror.org/017cjz748","country_code":"KR","type":"education","lineage":["https://openalex.org/I48566637"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Young Sim","raw_affiliation_strings":["School of Electrical and Computer Engineering, UNIST, Ulsan, Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, UNIST, Ulsan, Korea","institution_ids":["https://openalex.org/I48566637"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101886657"],"corresponding_institution_ids":["https://openalex.org/I48566637"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68516623,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"23","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9987000226974487,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9979000091552734,"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":0.8102161288261414},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7236068844795227},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7179146409034729},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.7031552791595459},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6461706757545471},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6315006613731384},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6245476007461548},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6082266569137573},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.439314603805542},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.43898436427116394},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.41787639260292053},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4104200303554535},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3499012291431427}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8102161288261414},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7236068844795227},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7179146409034729},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.7031552791595459},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6461706757545471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6315006613731384},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6245476007461548},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6082266569137573},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.439314603805542},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.43898436427116394},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.41787639260292053},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4104200303554535},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3499012291431427}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/apsipa.2016.7820823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2016.7820823","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarworks.unist.ac.kr:201301/35347","is_oa":false,"landing_page_url":"https://scholarworks.unist.ac.kr/handle/201301/35347","pdf_url":null,"source":{"id":"https://openalex.org/S4306401118","display_name":"Scholarworks@UNIST (Ulsan National Institute of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48566637","host_organization_name":"Ulsan National Institute of Science and Technology","host_organization_lineage":["https://openalex.org/I48566637"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"CONFERENCE"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W144883078","https://openalex.org/W1989723460","https://openalex.org/W2001054381","https://openalex.org/W2113137767","https://openalex.org/W2124351162","https://openalex.org/W2161511054","https://openalex.org/W6647586336"],"related_works":["https://openalex.org/W2356881624","https://openalex.org/W2394279717","https://openalex.org/W2364730859","https://openalex.org/W2359699469","https://openalex.org/W2386644571","https://openalex.org/W2619283684","https://openalex.org/W2383720950","https://openalex.org/W4281943322","https://openalex.org/W2948887454","https://openalex.org/W2185902295"],"abstract_inverted_index":{"Grabcut":[0,80,144],"is":[1],"an":[2,59,73,87],"efficient":[3],"image":[4,68,84],"segmentation":[5,75,98,173],"technique":[6],"which":[7],"facilitates":[8],"easy":[9],"user":[10],"interaction":[11],"by":[12,77,100,141,180],"locating":[13],"a":[14],"rectangular":[15],"bounding":[16],"box":[17],"to":[18,31,39,41,86],"include":[19],"the":[20,25,34,44,47,51,79,82,96,102,109,112,120,123,135,139,143,146,160,165,172,177,183],"foreground":[21,26,127,136],"objects.":[22],"However,":[23],"when":[24],"objects":[27,137,169],"exhibit":[28],"similar":[29],"colors":[30,153],"that":[32,159],"of":[33,50,62,111,122,151,168,185],"background,":[35],"it":[36],"often":[37],"fail":[38],"work":[40],"accurately":[42],"classify":[43],"pixels":[45,117,131],"within":[46],"interior":[48,121],"region":[49,61,184],"bonding":[52],"box.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57,92],"propose":[58],"adaptive":[60],"interest":[63],"selection":[64],"algorithm":[65,162],"for":[66],"Grabcut-based":[67],"segmentation.":[69],"We":[70,107],"first":[71],"obtain":[72],"initial":[74],"result":[76],"performing":[78,142],"on":[81],"depth":[83,97],"aligned":[85],"input":[88],"color":[89],"image.":[90],"Then":[91],"shrink":[93],"and":[94,104,118,138,154,170],"enlarge":[95],"mask":[99,114,125],"using":[101,145],"erosion":[103],"dilation":[105],"operations.":[106],"regard":[108,119],"outside":[110],"enlarged":[113],"as":[115,126],"background":[116,140],"shrunken":[124],"pixels.":[128],"The":[129],"remaining":[130],"are":[132],"classified":[133],"into":[134],"four-channel":[147],"Gaussian":[148],"mixture":[149],"model":[150],"RGB":[152],"depth.":[155],"Experimental":[156],"results":[157],"show":[158],"proposed":[161],"effectively":[163],"suppress":[164],"false":[166],"detection":[167],"improves":[171],"performance":[174],"compared":[175],"with":[176],"existing":[178],"algorithms":[179],"adaptively":[181],"selecting":[182],"interest.":[186]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}