{"id":"https://openalex.org/W2902294131","doi":"https://doi.org/10.23919/eusipco.2018.8553071","title":"Modeling the Pairwise Disparities in High Density Camera Arrays","display_name":"Modeling the Pairwise Disparities in High Density Camera Arrays","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2902294131","doi":"https://doi.org/10.23919/eusipco.2018.8553071","mag":"2902294131"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2018.8553071","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","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/A5008130391","display_name":"Ioan T\u0103bu\u015f","orcid":"https://orcid.org/0000-0003-3131-9551"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]},{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Ioan Tabus","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Tampere, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039865941","display_name":"Pekka Astola","orcid":"https://orcid.org/0000-0003-1042-4125"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]},{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Pekka Astola","raw_affiliation_strings":["Department of Signal Processing, Tampere University of Technology, Tampere, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":null,"issue":null,"first_page":"221","last_page":"225"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9965999722480774,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9955000281333923,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.8855770230293274},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.8510512113571167},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7234546542167664},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7118995785713196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5968061089515686},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5910775065422058},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5746805667877197},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5155222415924072},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4862886369228363},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.47533559799194336},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4615137577056885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4290543794631958},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3673398792743683},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3321836590766907},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2169082760810852},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15068450570106506}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.8855770230293274},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.8510512113571167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7234546542167664},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7118995785713196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5968061089515686},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5910775065422058},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5746805667877197},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5155222415924072},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4862886369228363},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.47533559799194336},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4615137577056885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4290543794631958},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3673398792743683},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3321836590766907},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2169082760810852},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15068450570106506},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2018.8553071","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2018.8553071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 26th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2149694199","https://openalex.org/W2200825767","https://openalex.org/W2441099548","https://openalex.org/W2556168980","https://openalex.org/W2787138665"],"related_works":["https://openalex.org/W1670332068","https://openalex.org/W2095618524","https://openalex.org/W2735770592","https://openalex.org/W2347413598","https://openalex.org/W2330863229","https://openalex.org/W71572444","https://openalex.org/W1997383766","https://openalex.org/W2350336482","https://openalex.org/W2010725720","https://openalex.org/W4310066305"],"abstract_inverted_index":{"We":[0,87,109],"discuss":[1],"in":[2,17,65,96,132,179,188],"this":[3,66],"paper":[4],"models":[5],"for":[6,82,100,151,194],"the":[7,14,48,111,114,118,137,152,158,177,181,189,198],"disparity":[8,59,63,76],"information":[9,64,120],"needed":[10],"when":[11],"pairwise":[12,74,124],"warping":[13,54],"angular":[15],"views":[16,41,50,57,144,184,190],"a":[18,36,97,123,155,170],"light":[19,31],"field":[20,32],"data":[21,33],"set":[22,37],"formed":[23],"of":[24,30,38,47,104,113,157,176,197],"N":[25],"views.":[26,108],"In":[27],"one":[28],"scenario":[29],"compression,":[34],"first":[35],"M":[39],"reference":[40,56],"is":[42,51,164,192],"encoded":[43],"and":[44,79,106,139,145,200],"then":[45],"each":[46,83],"remaining":[49],"predicted":[52,107],"by":[53,122,135,146],"several":[55,133,195],"using":[58],"information.":[60],"The":[61,127,160,174],"necessary":[62],"case":[67],"may":[68,129],"be":[69,94,130],"as":[70,72],"high":[71],"M(N-1)":[73],"view":[75],"maps,":[77],"estimated":[78],"transmitted":[80],"independently":[81],"pair":[84],"(reference,":[85],"target).":[86],"propose":[88],"an":[89],"estimation":[90,112,199],"model":[91,116,128,149,163,178],"which":[92],"can":[93],"used":[95],"flexible":[98],"way":[99],"any":[101],"selected":[102],"configuration":[103],"references":[105],"study":[110],"global":[115],"from":[117,154],"matching":[119,125],"provided":[121],"program.":[126],"defined":[131],"ways,":[134],"considering":[136],"vertical":[138],"horizontal":[140],"matches":[141],"at":[142,185],"various":[143],"allowing":[147],"different":[148],"parameters":[150],"regions":[153,161],"segmentation":[156],"scene.":[159],"based":[162],"shown":[165],"to":[166],"perform":[167],"better":[168],"than":[169],"single":[171],"region":[172],"model.":[173],"performance":[175],"synthesizing":[180],"unseen":[182],"color":[183],"specified":[186],"locations":[187],"array":[191],"presented":[193],"configurations":[196],"prediction":[201],"sets.":[202]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}