{"id":"https://openalex.org/W2158091675","doi":"https://doi.org/10.1109/icip.2009.5413752","title":"Accurate semantic image labeling by fast Geodesic Propagation","display_name":"Accurate semantic image labeling by fast Geodesic Propagation","publication_year":2009,"publication_date":"2009-11-01","ids":{"openalex":"https://openalex.org/W2158091675","doi":"https://doi.org/10.1109/icip.2009.5413752","mag":"2158091675"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2009.5413752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","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/A5101579463","display_name":"Xiaowu Chen","orcid":"https://orcid.org/0000-0001-8616-8231"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowu Chen","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, SCSE, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, SCSE, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025374137","display_name":"Dongyue Zhao","orcid":"https://orcid.org/0000-0002-0135-0614"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyue Zhao","raw_affiliation_strings":["State Key Laboratory of Virtual Reality Technology and Systems, SCSE, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Virtual Reality Technology and Systems, SCSE, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091164091","display_name":"Yibiao Zhao","orcid":"https://orcid.org/0000-0001-9517-1969"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibiao Zhao","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100412937","display_name":"Liang Lin","orcid":"https://orcid.org/0000-0003-2248-3755"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Lin","raw_affiliation_strings":["Department of Statistic, University of California, Los Angeles, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistic, University of California, Los Angeles, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3139,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.83759382,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4021","last_page":"4024"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9997000098228455,"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":0.9988999962806702,"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/geodesic","display_name":"Geodesic","score":0.7764809131622314},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6999358534812927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6328041553497314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6146264672279358},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5590300559997559},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.509304404258728},{"id":"https://openalex.org/keywords/connected-component-labeling","display_name":"Connected-component labeling","score":0.4999079704284668},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49082693457603455},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4813690781593323},{"id":"https://openalex.org/keywords/atlas","display_name":"Atlas (anatomy)","score":0.4597502052783966},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34800201654434204},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3022876977920532}],"concepts":[{"id":"https://openalex.org/C165818556","wikidata":"https://www.wikidata.org/wiki/Q213488","display_name":"Geodesic","level":2,"score":0.7764809131622314},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6999358534812927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6328041553497314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6146264672279358},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5590300559997559},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.509304404258728},{"id":"https://openalex.org/C58737948","wikidata":"https://www.wikidata.org/wiki/Q3136397","display_name":"Connected-component labeling","level":5,"score":0.4999079704284668},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49082693457603455},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4813690781593323},{"id":"https://openalex.org/C2776673561","wikidata":"https://www.wikidata.org/wiki/Q655357","display_name":"Atlas (anatomy)","level":2,"score":0.4597502052783966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34800201654434204},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3022876977920532},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2009.5413752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","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":13,"referenced_works":["https://openalex.org/W128019999","https://openalex.org/W1238092070","https://openalex.org/W2017313218","https://openalex.org/W2054279472","https://openalex.org/W2063266501","https://openalex.org/W2119823327","https://openalex.org/W2122006243","https://openalex.org/W2134839354","https://openalex.org/W2143516773","https://openalex.org/W2143941221","https://openalex.org/W2149954907","https://openalex.org/W2168463767","https://openalex.org/W6678000420"],"related_works":["https://openalex.org/W234638232","https://openalex.org/W1991239220","https://openalex.org/W1990491759","https://openalex.org/W4312948892","https://openalex.org/W1985266213","https://openalex.org/W1124744518","https://openalex.org/W2097164998","https://openalex.org/W2103507220","https://openalex.org/W2750017896","https://openalex.org/W2951798667"],"abstract_inverted_index":{"Motivated":[0],"by":[1,49],"recently":[2],"raised":[3],"image":[4,22,95,105],"semantic":[5,79,124],"labeling":[6,80],"problem,":[7],"this":[8],"paper":[9],"studies":[10],"a":[11,25,59,113],"fast":[12],"Geodesic":[13],"Propagation":[14],"(GP)":[15],"algorithm":[16,99],"that":[17],"integrates":[18],"recognition":[19,30,70],"proposal":[20,31,47,71],"and":[21,65,133],"compatibility":[23],"into":[24],"graphical":[26],"representation.":[27],"Given":[28],"the":[29,34,36,63,69,75,78,85,92,117,141],"map":[32],"of":[33,88,94,102,106],"image,":[35],"initial":[37,86],"seeds":[38,87],"are":[39],"selected":[40],"as":[41],"confident":[42],"pixels":[43,108],"standing":[44],"on":[45,58,74,121,130,136],"local":[46],"peaks":[48],"Mean-shift":[50],"algorithm.":[51],"The":[52],"geodesic":[53,76],"distance":[54],"is":[55,81,100],"then":[56],"defined":[57],"hybrid":[60],"manifold,":[61],"combining":[62],"color":[64],"boundary":[66],"features":[67],"with":[68],"map.":[72],"Based":[73],"distance,":[77],"simultaneously":[82],"propagated":[83],"from":[84],"all":[89],"classes":[90],"to":[91,139],"rest":[93],"pixels.":[96],"This":[97],"inference":[98],"capable":[101],"multi-labeling":[103],"an":[104],"2-mega":[107],"in":[109],"one":[110],"second":[111],"(with":[112],"common":[114],"PC).":[115],"In":[116],"experiment,":[118],"we":[119],"test":[120],"21":[122],"generic":[123],"categories":[125,135],"(sky,":[126],"road,":[127],"grass":[128],"...)":[129],"MSRC":[131],"dataset,":[132],"17":[134],"LHI":[137],"dataset":[138],"evaluate":[140],"performance.":[142]},"counts_by_year":[{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}