{"id":"https://openalex.org/W2081925071","doi":"https://doi.org/10.1109/icme.2007.4285055","title":"Multi-Scale Gabor Phase-Based Stereo Matching using Graph Cuts","display_name":"Multi-Scale Gabor Phase-Based Stereo Matching using Graph Cuts","publication_year":2007,"publication_date":"2007-07-01","ids":{"openalex":"https://openalex.org/W2081925071","doi":"https://doi.org/10.1109/icme.2007.4285055","mag":"2081925071"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2007.4285055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2007.4285055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia and Expo, 2007 IEEE International Conference on","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/A5101798245","display_name":"Peifeng Zhang","orcid":"https://orcid.org/0009-0000-5422-7460"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peifeng Zhang","raw_affiliation_strings":["Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","Shanghai Jiao Tong University, Shanghai"],"affiliations":[{"raw_affiliation_string":"Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101848162","display_name":"Yi Xu","orcid":"https://orcid.org/0000-0002-5280-6132"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Xu","raw_affiliation_strings":["Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, 200240, China. xuyi@sjtu.edu.cn"],"affiliations":[{"raw_affiliation_string":"Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, 200240, China. xuyi@sjtu.edu.cn","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019708391","display_name":"Xiaokang Yang","orcid":"https://orcid.org/0000-0003-4029-3322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaokang Yang","raw_affiliation_strings":["Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","Institute of Image Communication & Information Processing, Shanghai Jiao Tong University, Shanghai 200240, China, xkyang@sjtu.edu.cn"],"affiliations":[{"raw_affiliation_string":"Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institute of Image Communication & Information Processing, Shanghai Jiao Tong University, Shanghai 200240, China, xkyang@sjtu.edu.cn","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021735908","display_name":"Leonardo Traversoni","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leonardo Traversoni","raw_affiliation_strings":["Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, 200240, China. 1td@xanum.uam.mx"],"affiliations":[{"raw_affiliation_string":"Institute of Image Communication and Information Processing, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, Shanghai, 200240, China. 1td@xanum.uam.mx","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101798245"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12478677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"24","issue":null,"first_page":"1934","last_page":"1937"},"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":0.9972000122070312,"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":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.6646450757980347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6386862993240356},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5825703740119934},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.5408738851547241},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5199660062789917},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45838186144828796},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.4480305016040802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4388166666030884},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4239211976528168},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.41451576352119446},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40498653054237366},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.14355608820915222},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09385308623313904},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08001828193664551},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07126647233963013}],"concepts":[{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.6646450757980347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6386862993240356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5825703740119934},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.5408738851547241},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5199660062789917},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45838186144828796},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.4480305016040802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4388166666030884},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4239211976528168},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.41451576352119446},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40498653054237366},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.14355608820915222},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09385308623313904},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08001828193664551},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07126647233963013},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2007.4285055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2007.4285055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Multimedia and Expo, 2007 IEEE International Conference on","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":11,"referenced_works":["https://openalex.org/W1520822062","https://openalex.org/W1570637365","https://openalex.org/W2037297495","https://openalex.org/W2040353450","https://openalex.org/W2083467847","https://openalex.org/W2104974755","https://openalex.org/W2109681684","https://openalex.org/W2151646056","https://openalex.org/W2169282664","https://openalex.org/W2170934089","https://openalex.org/W6660519121"],"related_works":["https://openalex.org/W2387690017","https://openalex.org/W29916882","https://openalex.org/W2029983961","https://openalex.org/W2021544484","https://openalex.org/W2171149362","https://openalex.org/W2181395181","https://openalex.org/W2183780938","https://openalex.org/W2169282664","https://openalex.org/W1567641598","https://openalex.org/W2071060869"],"abstract_inverted_index":{"In":[0],"this":[1,71],"paper,":[2],"we":[3,43,83],"present":[4],"a":[5,46],"multi-scale":[6,51],"Gabor":[7,52],"phase-based":[8,18],"stereo":[9,19,125],"matching":[10,20,126,136],"scheme.":[11],"Unlike":[12],"the":[13,16,27,36,40,57,78,85,115,118,123],"mechanism":[14],"in":[15,97,106,138,146],"existing":[17],"methods,":[21,127],"where":[22],"disparity":[23,81,104],"is":[24,66,111],"formulated":[25],"as":[26,88],"ratio":[28],"of":[29,60,80,117],"phase":[30,61],"difference":[31],"between":[32],"two":[33],"views":[34],"to":[35,54,113],"local":[37],"frequency":[38,98],"at":[39],"given":[41],"position,":[42],"set":[44],"up":[45],"robust":[47,72],"data":[48,73],"measure":[49],"from":[50],"phases":[53],"greatly":[55],"alleviate":[56],"negative":[58],"effect":[59],"singularity.":[62],"A":[63],"cost":[64,86,95,119],"function":[65,87],"then":[67],"advanced":[68],"based":[69],"on":[70],"measure.":[74],"To":[75,100],"further":[76],"improve":[77],"accuracy":[79],"estimation,":[82],"formulate":[84],"three":[89],"coupled":[90],"Markov":[91],"Random":[92],"Field":[93],"(MRF)":[94],"terms":[96],"domain.":[99],"obtain":[101],"globally":[102],"optimized":[103],"map":[105],"wide":[107],"range,":[108],"graph":[109],"cut":[110],"employed":[112],"perform":[114],"minimization":[116],"function.":[120],"Compared":[121],"with":[122],"state-of-the-art":[124],"experimental":[128],"results":[129,145],"demonstrate":[130],"that":[131],"our":[132],"approach":[133],"gets":[134],"comparable":[135],"performance":[137],"indoor":[139],"scenes":[140],"and":[141],"achieves":[142],"much":[143],"better":[144],"aerial":[147],"scenes.":[148]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
