{"id":"https://openalex.org/W2060211434","doi":"https://doi.org/10.1109/icip.2013.6738462","title":"Spatiotemporal stereo matching for dynamic scenes with temporal disparity variation","display_name":"Spatiotemporal stereo matching for dynamic scenes with temporal disparity variation","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2060211434","doi":"https://doi.org/10.1109/icip.2013.6738462","mag":"2060211434"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","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/A5102033092","display_name":"Yong-Ho Shin","orcid":null},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongho Shin","raw_affiliation_strings":["Gwangju Institute of Science and Technology (GIST), Republic of Korea","Gwangju Institute of Science and Technology, GIST, Gwangju, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gwangju Institute of Science and Technology (GIST), Republic of Korea","institution_ids":["https://openalex.org/I39534123"]},{"raw_affiliation_string":"Gwangju Institute of Science and Technology, GIST, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113931494","display_name":"Kuk\u2010Jin Yoon","orcid":null},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kuk-Jin Yoon","raw_affiliation_strings":["Gwangju Institute of Science and Technology (GIST), Republic of Korea","Gwangju Institute of Science and Technology, GIST, Gwangju, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gwangju Institute of Science and Technology (GIST), Republic of Korea","institution_ids":["https://openalex.org/I39534123"]},{"raw_affiliation_string":"Gwangju Institute of Science and Technology, GIST, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2242","last_page":"2246"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9968000054359436,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9966999888420105,"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":0.6910937428474426},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6652028560638428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6613587737083435},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5677587389945984},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.54848712682724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5380468368530273},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4964907765388489},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4925573468208313},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.4906531870365143},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.48428839445114136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43094560503959656},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33339428901672363},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21648353338241577},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21256771683692932},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.0848771333694458},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0727253258228302}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6910937428474426},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6652028560638428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6613587737083435},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5677587389945984},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.54848712682724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5380468368530273},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4964907765388489},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4925573468208313},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.4906531870365143},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.48428839445114136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43094560503959656},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33339428901672363},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21648353338241577},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21256771683692932},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.0848771333694458},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0727253258228302}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2013.6738462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"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/W1674866864","https://openalex.org/W1967349994","https://openalex.org/W1968799614","https://openalex.org/W2088692258","https://openalex.org/W2090518410","https://openalex.org/W2097368509","https://openalex.org/W2101092098","https://openalex.org/W2127363007","https://openalex.org/W2130808355","https://openalex.org/W2135878862","https://openalex.org/W2136660755","https://openalex.org/W2140200866","https://openalex.org/W2150066425","https://openalex.org/W2156842971","https://openalex.org/W2180873826","https://openalex.org/W2330337224","https://openalex.org/W4233754687","https://openalex.org/W4285719527","https://openalex.org/W6673243404","https://openalex.org/W6674764965","https://openalex.org/W6678966091","https://openalex.org/W6680241546","https://openalex.org/W6680504032","https://openalex.org/W6680857110"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2319693127","https://openalex.org/W308539617","https://openalex.org/W2072263576","https://openalex.org/W2474567666","https://openalex.org/W1940044583","https://openalex.org/W2806903871","https://openalex.org/W4320802053"],"abstract_inverted_index":{"When":[0],"there":[1],"exists":[2],"camera":[3],"and":[4,41,66,88,120,141],"scene":[5],"motion,":[6],"the":[7,24,47,53,59,73,95,101,136,146],"disparity":[8,20,65,87,143],"of":[9,26,104],"a":[10,35,42,67,130],"pixel":[11],"temporally":[12],"varies":[13],"as":[14],"time":[15],"goes":[16],"on.":[17],"Such":[18],"temporal":[19,84],"variation":[21],"(TDV)":[22],"degrades":[23],"performance":[25],"spatiotemporal":[27,75],"stereo":[28],"matching.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,111],"devise":[34],"robust":[36],"similarity":[37,60],"measure":[38],"against":[39],"TDV,":[40],"suitable":[43],"optimization":[44],"technique":[45,78],"for":[46,63],"proposed":[48,137],"measure.":[49],"We":[50,70],"first":[51],"design":[52],"window-based":[54],"matching":[55],"cost":[56],"to":[57,79,99],"evaluate":[58],"between":[61],"pixels":[62],"given":[64],"TDV":[68,89,109],"value.":[69],"also":[71],"present":[72],"improved":[74],"guided-filter-based":[76],"aggregation":[77],"gather":[80],"match":[81],"costs":[82],"with":[83,126],"weights.":[85],"The":[86],"maps":[90,144],"are":[91],"then":[92],"obtained":[93],"by":[94],"global":[96],"optimization.":[97],"Here,":[98],"handle":[100],"large":[102],"number":[103],"labels":[105],"(disparity":[106],"levels":[107],"\u00d7":[108],"levels),":[110],"use":[112],"dual-layer":[113],"belief":[114,127],"propagation":[115,128],"that":[116],"requires":[117],"less":[118],"computation":[119],"memory":[121],"while":[122],"producing":[123],"comparable":[124],"results":[125,134],"using":[129],"single":[131],"layer.":[132],"Experimental":[133],"show":[135],"method":[138],"yields":[139],"consistent":[140],"accurate":[142],"under":[145],"TDV.":[147]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}