{"id":"https://openalex.org/W2068620284","doi":"https://doi.org/10.1109/icpr.2008.4761101","title":"Local stereo matching with 3D adaptive cost aggregation for slanted surface modeling and sub-pixel accuracy","display_name":"Local stereo matching with 3D adaptive cost aggregation for slanted surface modeling and sub-pixel accuracy","publication_year":2008,"publication_date":"2008-12-01","ids":{"openalex":"https://openalex.org/W2068620284","doi":"https://doi.org/10.1109/icpr.2008.4761101","mag":"2068620284"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2008.4761101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761101","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","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/A5100694328","display_name":"Yilei Zhang","orcid":"https://orcid.org/0000-0003-4296-1857"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Yilei Zhang","raw_affiliation_strings":["University of Alberta","University of Alberta,, AB,, Canada"],"affiliations":[{"raw_affiliation_string":"University of Alberta","institution_ids":["https://openalex.org/I154425047"]},{"raw_affiliation_string":"University of Alberta,, AB,, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109011312","display_name":"Minglun Gong","orcid":"https://orcid.org/0000-0001-5820-5381"},"institutions":[{"id":"https://openalex.org/I130438778","display_name":"Memorial University of Newfoundland","ror":"https://ror.org/04haebc03","country_code":"CA","type":"education","lineage":["https://openalex.org/I130438778"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Minglun Gong","raw_affiliation_strings":["Memorial University of Newfoundland","Memorial University of Newfoundland, Canada"],"affiliations":[{"raw_affiliation_string":"Memorial University of Newfoundland","institution_ids":["https://openalex.org/I130438778"]},{"raw_affiliation_string":"Memorial University of Newfoundland, Canada","institution_ids":["https://openalex.org/I130438778"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081300658","display_name":"Yee\u2010Hong Yang","orcid":"https://orcid.org/0000-0002-7194-3327"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yee-Hong Yang","raw_affiliation_strings":["University of Alberta","University of Alberta,, AB,, Canada"],"affiliations":[{"raw_affiliation_string":"University of Alberta","institution_ids":["https://openalex.org/I154425047"]},{"raw_affiliation_string":"University of Alberta,, AB,, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100694328"],"corresponding_institution_ids":["https://openalex.org/I154425047"],"apc_list":null,"apc_paid":null,"fwci":3.4531,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.92719486,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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":1.0,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9987999796867371,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/pixel","display_name":"Pixel","score":0.8719664812088013},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.662507176399231},{"id":"https://openalex.org/keywords/plane","display_name":"Plane (geometry)","score":0.640365719795227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6293835639953613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6249164938926697},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6177850961685181},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.5670827031135559},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.5553476214408875},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.5359047055244446},{"id":"https://openalex.org/keywords/image-plane","display_name":"Image plane","score":0.5021007061004639},{"id":"https://openalex.org/keywords/binocular-disparity","display_name":"Binocular disparity","score":0.5003318786621094},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3307943344116211},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30846136808395386},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.16409417986869812}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.8719664812088013},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.662507176399231},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.640365719795227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6293835639953613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6249164938926697},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6177850961685181},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.5670827031135559},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.5553476214408875},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.5359047055244446},{"id":"https://openalex.org/C120515352","wikidata":"https://www.wikidata.org/wiki/Q2564580","display_name":"Image plane","level":3,"score":0.5021007061004639},{"id":"https://openalex.org/C90790637","wikidata":"https://www.wikidata.org/wiki/Q11681118","display_name":"Binocular disparity","level":3,"score":0.5003318786621094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3307943344116211},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30846136808395386},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.16409417986869812},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2008.4761101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761101","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.214.3610","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.3610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://figment.cse.usf.edu/~sfefilat/data/papers/MoCT2.1.pdf","raw_type":"text"}],"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/W1590360666","https://openalex.org/W2104974755","https://openalex.org/W2106257280","https://openalex.org/W2112421488","https://openalex.org/W2123782500","https://openalex.org/W2157431410"],"related_works":["https://openalex.org/W98522529","https://openalex.org/W3179676481","https://openalex.org/W2102713649","https://openalex.org/W4234766120","https://openalex.org/W2069381083","https://openalex.org/W855857303","https://openalex.org/W2464663160","https://openalex.org/W2977038053","https://openalex.org/W2414031639","https://openalex.org/W2047447967"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3],"new":[4],"local":[5],"binocular":[6],"stereo":[7],"algorithm":[8],"which":[9,43],"takes":[10],"into":[11],"consideration":[12],"plane":[13,46,71],"fitting":[14],"at":[15,103],"the":[16,32,44,56,59,68,75,89,92,108,111,118],"per-pixel":[17],"level.":[18],"Two":[19],"disparity":[20,40,45,70,97,112],"calculation":[21],"passes":[22],"are":[23,34,51],"used.":[24],"The":[25,96,114],"first":[26],"pass":[27],"assumes":[28],"that":[29],"surfaces":[30],"in":[31],"scene":[33],"fronto-parallel":[35,76],"and":[36,53],"generates":[37],"an":[38],"initial":[39],"map,":[41],"from":[42],"orientations":[47],"of":[48,91,110,120],"all":[49],"pixels":[50],"extracted":[52],"refined.":[54],"In":[55],"second":[57],"pass,":[58],"cost":[60],"aggregation":[61],"for":[62],"each":[63],"pixel":[64],"is":[65,85,100],"conducted":[66],"along":[67],"estimated":[69],"orientations,":[72],"rather":[73],"than":[74],"ones.":[77],"Large":[78],"window":[79],"size":[80],"with":[81],"adaptive":[82],"support":[83],"weights":[84],"used":[86],"to":[87,106],"ensure":[88],"effectiveness":[90],"slanted":[93],"surface":[94],"modeling.":[95],"search":[98],"space":[99],"also":[101],"quantized":[102],"sub-pixel":[104],"level":[105],"improve":[107],"accuracy":[109],"results.":[113],"experimental":[115],"results":[116],"demonstrate":[117],"validity":[119],"our":[121],"presented":[122],"approach.":[123]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
