{"id":"https://openalex.org/W1511016087","doi":"https://doi.org/10.1109/chinasip.2015.7230398","title":"A local stereo matching approach using adaptive weight boundary","display_name":"A local stereo matching approach using adaptive weight boundary","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1511016087","doi":"https://doi.org/10.1109/chinasip.2015.7230398","mag":"1511016087"},"language":"en","primary_location":{"id":"doi:10.1109/chinasip.2015.7230398","is_oa":false,"landing_page_url":"https://doi.org/10.1109/chinasip.2015.7230398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP)","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/A5020388904","display_name":"Kongfen Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kongfen Zhu","raw_affiliation_strings":["School of Electronics and Information Engineering, Taiyuan University of Science and Technology","[School of Electronics and Information Engineering, Taiyuan University of Science and Technology]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Taiyuan University of Science and Technology","institution_ids":["https://openalex.org/I46305995"]},{"raw_affiliation_string":"[School of Electronics and Information Engineering, Taiyuan University of Science and Technology]","institution_ids":["https://openalex.org/I46305995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075856716","display_name":"Xiong Zhang","orcid":"https://orcid.org/0000-0001-9905-281X"},"institutions":[{"id":"https://openalex.org/I46305995","display_name":"Taiyuan University of Science and Technology","ror":"https://ror.org/01wcbdc92","country_code":"CN","type":"education","lineage":["https://openalex.org/I46305995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiong Zhang","raw_affiliation_strings":["School of Electronics and Information Engineering, Taiyuan University of Science and Technology","[School of Electronics and Information Engineering, Taiyuan University of Science and Technology]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Taiyuan University of Science and Technology","institution_ids":["https://openalex.org/I46305995"]},{"raw_affiliation_string":"[School of Electronics and Information Engineering, Taiyuan University of Science and Technology]","institution_ids":["https://openalex.org/I46305995"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I46305995"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"235","last_page":"239"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9950000047683716,"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":0.7061716318130493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6933302283287048},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.686618983745575},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6419972777366638},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5930141806602478},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5401870012283325},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.529190182685852},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5281231999397278},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5266159176826477},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49478834867477417},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4385881721973419},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4162563681602478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25832343101501465},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07451891899108887}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7061716318130493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6933302283287048},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.686618983745575},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6419972777366638},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5930141806602478},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5401870012283325},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.529190182685852},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5281231999397278},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5266159176826477},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49478834867477417},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4385881721973419},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4162563681602478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25832343101501465},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07451891899108887},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/chinasip.2015.7230398","is_oa":false,"landing_page_url":"https://doi.org/10.1109/chinasip.2015.7230398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1968799614","https://openalex.org/W1996126470","https://openalex.org/W1999625467","https://openalex.org/W2000083214","https://openalex.org/W2067191022","https://openalex.org/W2079495650","https://openalex.org/W2080444166","https://openalex.org/W2104974755","https://openalex.org/W2112421488","https://openalex.org/W2113873920","https://openalex.org/W2123782500","https://openalex.org/W2156585821"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2113096305","https://openalex.org/W2171299904","https://openalex.org/W1522196789"],"abstract_inverted_index":{"A":[0],"new":[1],"region-based":[2],"local":[3,15,42],"stereo":[4,16],"matching":[5,77],"algorithm":[6],"with":[7,45,113],"accurate":[8,36],"disparity":[9,29],"estimation":[10],"is":[11,23,48,92],"proposed.":[12],"For":[13],"the":[14,26,54,57,63,66,70,74,85,96,99,106],"matching,":[17],"finding":[18],"an":[19,35],"appropriate":[20],"support":[21,37,71],"window":[22],"crucial":[24],"to":[25,33,95],"performance":[27,111],"of":[28,56,65,98],"estimation.":[30,101],"In":[31],"order":[32],"generate":[34],"region,":[38],"a":[39],"modified":[40],"cross-based":[41],"approach":[43],"combined":[44],"mean-shift":[46],"segmentation":[47],"performed.":[49],"We":[50],"then":[51],"further":[52],"improve":[53],"reliability":[55],"aggregation":[58],"cost":[59],"by":[60,82],"adaptively":[61],"adjusting":[62],"weights":[64],"boundary":[67],"pixels":[68],"in":[69],"region.":[72],"With":[73],"stable":[75],"aggregating":[76],"cost,":[78],"some":[79],"noises":[80],"caused":[81],"outliers":[83],"at":[84],"object":[86],"boundaries":[87],"can":[88],"be":[89],"removed,":[90],"which":[91],"greatly":[93],"beneficial":[94],"quality":[97],"depth":[100],"Experimental":[102],"results":[103],"show":[104],"that":[105],"proposed":[107],"method":[108],"achieves":[109],"superior":[110],"compared":[112],"other":[114],"state-of-the-art":[115],"methods.":[116]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}