{"id":"https://openalex.org/W2070582758","doi":"https://doi.org/10.1109/ic3d.2011.6584384","title":"A fast segmentation-driven algorithm for accurate stereo correspondence","display_name":"A fast segmentation-driven algorithm for accurate stereo correspondence","publication_year":2011,"publication_date":"2011-12-01","ids":{"openalex":"https://openalex.org/W2070582758","doi":"https://doi.org/10.1109/ic3d.2011.6584384","mag":"2070582758"},"language":"en","primary_location":{"id":"doi:10.1109/ic3d.2011.6584384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3d.2011.6584384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on 3D Imaging (IC3D)","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/A5072569849","display_name":"Stefano Mattoccia","orcid":"https://orcid.org/0000-0002-3681-7704"},"institutions":[{"id":"https://openalex.org/I9360294","display_name":"University of Bologna","ror":"https://ror.org/01111rn36","country_code":"IT","type":"education","lineage":["https://openalex.org/I9360294"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Stefano Mattoccia","raw_affiliation_strings":["Department of Electronics, Computer Sciences and Systems, University of Bologna, Bologna, Italy","Dept. of Electron., Comput. Sci. & Syst., Univ. of Bologna, Bologna, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics, Computer Sciences and Systems, University of Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]},{"raw_affiliation_string":"Dept. of Electron., Comput. Sci. & Syst., Univ. of Bologna, Bologna, Italy","institution_ids":["https://openalex.org/I9360294"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072573955","display_name":"Leonardo De-Maeztu","orcid":"https://orcid.org/0009-0009-9058-3425"},"institutions":[{"id":"https://openalex.org/I175051016","display_name":"Universidad P\u00fablica de Navarra (UPNA)","ror":"https://ror.org/02z0cah89","country_code":"ES","type":"education","lineage":["https://openalex.org/I175051016"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Leonardo De-Maeztu","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Public University of Navarre, Pamplona, Spain","Dept. of Electr. & Electron. Eng., Public Univ. of Navarre, Pamplona, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Public University of Navarre, Pamplona, Spain","institution_ids":["https://openalex.org/I175051016"]},{"raw_affiliation_string":"Dept. of Electr. & Electron. Eng., Public Univ. of Navarre, Pamplona, Spain","institution_ids":["https://openalex.org/I175051016"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","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/T10531","display_name":"Advanced Vision and Imaging","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/T10627","display_name":"Advanced Image and Video Retrieval 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/T11019","display_name":"Image Enhancement Techniques","score":0.9990000128746033,"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/computer-science","display_name":"Computer science","score":0.8435518145561218},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.6927986741065979},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5944818258285522},{"id":"https://openalex.org/keywords/simplicity","display_name":"Simplicity","score":0.586127758026123},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5755623579025269},{"id":"https://openalex.org/keywords/footprint","display_name":"Footprint","score":0.4908224046230316},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.47504639625549316},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43938037753105164},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.42844662070274353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34880584478378296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8435518145561218},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.6927986741065979},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5944818258285522},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.586127758026123},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5755623579025269},{"id":"https://openalex.org/C132943942","wikidata":"https://www.wikidata.org/wiki/Q2562511","display_name":"Footprint","level":2,"score":0.4908224046230316},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.47504639625549316},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43938037753105164},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.42844662070274353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34880584478378296},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ic3d.2011.6584384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic3d.2011.6584384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on 3D Imaging (IC3D)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.221.5929","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.221.5929","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.vision.deis.unibo.it/smatt/Papers/IC3D2011/IC3D_FSD_2011.pdf","raw_type":"text"},{"id":"pmh:oai:cris.unibo.it:11585/124990","is_oa":false,"landing_page_url":"http://ieeexplore.ieee.org/document/6584384/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402579","display_name":"Archivio istituzionale della ricerca (Alma Mater Studiorum Universit\u00e0 di Bologna)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210117483","host_organization_name":"Istituto di Ematologia di Bologna","host_organization_lineage":["https://openalex.org/I4210117483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1520110625","https://openalex.org/W1590360666","https://openalex.org/W2011807137","https://openalex.org/W2067191022","https://openalex.org/W2097368509","https://openalex.org/W2104974755","https://openalex.org/W2105116449","https://openalex.org/W2113873920","https://openalex.org/W2123782500","https://openalex.org/W2125186487","https://openalex.org/W2131948010","https://openalex.org/W2143425433","https://openalex.org/W2150737612","https://openalex.org/W2150802895","https://openalex.org/W2154234100","https://openalex.org/W2157431410","https://openalex.org/W2163883567","https://openalex.org/W2169363967","https://openalex.org/W2362808110","https://openalex.org/W4253999777","https://openalex.org/W6635314138","https://openalex.org/W6674764965","https://openalex.org/W6675461436","https://openalex.org/W6685059715"],"related_works":["https://openalex.org/W2368019753","https://openalex.org/W2333930193","https://openalex.org/W2737356002","https://openalex.org/W2246241526","https://openalex.org/W4301122218","https://openalex.org/W2374150061","https://openalex.org/W2081340182","https://openalex.org/W1522196789","https://openalex.org/W3137434606","https://openalex.org/W4372263373"],"abstract_inverted_index":{"Recent":[0],"cost":[1,51,87,133],"aggregation":[2,52,88,134],"strategies":[3,53,135],"that":[4,92],"adapt":[5],"their":[6,63],"weights":[7],"to":[8,14,18,44,95,99,111],"image":[9],"content":[10],"enabled":[11],"local":[12,56],"algorithms":[13,22,57],"obtain":[15,96],"results":[16,97],"comparable":[17,67,98],"those":[19,72],"of":[20,37,48,73,120,139],"global":[21,45,74],"based":[23,89],"on":[24,90],"more":[25,103],"complex":[26],"disparity":[27],"optimization":[28],"methods.":[29],"Unfortunately,":[30],"despite":[31],"the":[32,49,137],"potential":[33],"advantages":[34],"in":[35,55,125],"terms":[36],"memory":[38],"footprint":[39],"and":[40,68,85],"algorithmic":[41],"simplicity":[42],"compared":[43],"algorithms,":[46],"most":[47],"state-of-the-art":[50,100,132],"deployed":[54],"are":[58],"extremely":[59],"slow.":[60],"In":[61,76],"fact,":[62],"execution":[64,106],"time":[65,107],"is":[66,116],"often":[69],"worse":[70],"than":[71],"approaches.":[75],"this":[77],"paper":[78],"we":[79],"propose":[80],"a":[81],"framework":[82],"for":[83],"accurate":[84],"fast":[86],"segmentation":[91],"allows":[93],"us":[94],"approaches":[101],"much":[102],"efficiently":[104],"(the":[105],"drops":[108],"from":[109],"minutes":[110],"seconds).":[112],"A":[113],"further":[114],"speed-up":[115],"achieved":[117],"taking":[118],"advantage":[119],"multi-core":[121],"capabilities":[122],"available":[123],"nowadays":[124],"almost":[126],"any":[127],"processor.":[128],"The":[129],"comparison":[130],"with":[131],"highlights":[136],"effectiveness":[138],"our":[140],"proposal.":[141]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}