{"id":"https://openalex.org/W3204966531","doi":"https://doi.org/10.1109/bmsb53066.2021.9547077","title":"RGB-Based No-Reference Depth Map Quality Assessment","display_name":"RGB-Based No-Reference Depth Map Quality Assessment","publication_year":2021,"publication_date":"2021-08-04","ids":{"openalex":"https://openalex.org/W3204966531","doi":"https://doi.org/10.1109/bmsb53066.2021.9547077","mag":"3204966531"},"language":"en","primary_location":{"id":"doi:10.1109/bmsb53066.2021.9547077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb53066.2021.9547077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","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/A5059912382","display_name":"Zhuo Zhao","orcid":"https://orcid.org/0000-0002-4449-2663"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuo Zhao","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, P.R. China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, P.R. China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037055449","display_name":"Meng Yang","orcid":"https://orcid.org/0000-0002-0525-5059"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Yang","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, P.R. China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, P.R. China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059912382"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12787582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9994999766349792,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9994999766349792,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9990000128746033,"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":0.9976999759674072,"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/depth-map","display_name":"Depth map","score":0.8366248607635498},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7401545643806458},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6906338930130005},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.684140145778656},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6639513373374939},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.631689727306366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6130485534667969},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5368329286575317},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.48753806948661804},{"id":"https://openalex.org/keywords/depth-perception","display_name":"Depth perception","score":0.44923830032348633},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.43845245242118835},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4331352710723877},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.41600847244262695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33267468214035034},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2998402714729309},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08768239617347717},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.0756082832813263}],"concepts":[{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.8366248607635498},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7401545643806458},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6906338930130005},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.684140145778656},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6639513373374939},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.631689727306366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6130485534667969},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5368329286575317},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.48753806948661804},{"id":"https://openalex.org/C52672216","wikidata":"https://www.wikidata.org/wiki/Q1749840","display_name":"Depth perception","level":3,"score":0.44923830032348633},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.43845245242118835},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4331352710723877},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.41600847244262695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33267468214035034},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2998402714729309},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08768239617347717},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.0756082832813263},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bmsb53066.2021.9547077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmsb53066.2021.9547077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7350781410","display_name":null,"funder_award_id":"61627811,91748208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1972491016","https://openalex.org/W1982471090","https://openalex.org/W1998823483","https://openalex.org/W1999187624","https://openalex.org/W2099308462","https://openalex.org/W2102166818","https://openalex.org/W2105029388","https://openalex.org/W2112421488","https://openalex.org/W2119781527","https://openalex.org/W2128605760","https://openalex.org/W2129285461","https://openalex.org/W2132541137","https://openalex.org/W2143447765","https://openalex.org/W2257456433","https://openalex.org/W2769132445","https://openalex.org/W3153451041","https://openalex.org/W6692226854"],"related_works":["https://openalex.org/W3102673927","https://openalex.org/W2327954668","https://openalex.org/W2771419958","https://openalex.org/W1986056272","https://openalex.org/W3202440119","https://openalex.org/W2312573994","https://openalex.org/W2605482345","https://openalex.org/W4307472573","https://openalex.org/W2741636507","https://openalex.org/W36187127"],"abstract_inverted_index":{"Depth":[0],"maps":[1,23],"play":[2],"an":[3],"important":[4],"role":[5],"in":[6,43,98,128,150,236],"computer":[7],"vision":[8],"and":[9,77,103,157,180,186,253],"robotics":[10],"tasks.":[11,45],"However,":[12],"it":[13,84,254],"is":[14,33,143,160,201],"difficult":[15],"to":[16,52,93,145],"obtain":[17],"ground":[18,250],"truth":[19,251],"(GT)":[20],"of":[21,56,62,112,132,166,174,193,218,232,264],"depth":[22,26,38,57,70,99,134,176,196,224,265],"by":[24,120,155],"either":[25],"sensors":[27],"or":[28],"calculation":[29],"methods.":[30],"Therefore,":[31],"there":[32],"a":[34,49,91,140],"great":[35],"need":[36],"for":[37],"quality":[39,55,110,164,190,226,246,263],"assessment":[40,172,191,216,227,230,247],"without":[41],"GT":[42],"relevant":[44],"This":[46],"paper":[47,238],"proposes":[48],"new":[50],"method":[51,200,234,258],"assess":[53,261],"the":[54,60,69,81,86,95,105,109,113,117,122,125,129,133,138,147,151,158,163,167,171,175,181,189,194,204,215,219,229,233,240,244,262],"map":[58,71,100,135,177,225],"with":[59,214,243,249],"guidance":[61],"its":[63],"associated":[64],"RGB":[65,88],"image,":[66],"which":[67],"divides":[68],"into":[72],"two":[73,221],"parts:":[74],"structure":[75,101,114,178],"area":[76,131,153,179,183],"smooth":[78,130,152,168,182],"area.":[79,115,169],"On":[80,116],"one":[82],"hand,":[83,119],"uses":[85],"same-view":[87],"image":[89],"as":[90,108,162,188],"reference":[92],"detect":[94,146],"error":[96,148],"pixels":[97,149],"area,":[102],"calculates":[104],"objective":[106,245],"index":[107],"score":[111,165],"other":[118,220],"using":[121],"feature":[123],"that":[124,212,256],"pixel":[126],"values":[127],"are":[136,184],"all":[137],"same,":[139],"sliding":[141],"window":[142],"set":[144],"affected":[154],"noise,":[156],"metric":[159],"calculated":[161],"Finally,":[170],"scores":[173],"weighted":[185],"integrated":[187],"result":[192],"entire":[195],"map.":[197],"The":[198],"proposed":[199,235],"tested":[202],"on":[203],"Middlebury":[205],"dataset.":[206],"It":[207],"can":[208,259],"be":[209],"clearly":[210],"seen":[211],"compared":[213],"results":[217,231,248],"existing":[222],"no-reference":[223],"methods,":[228],"this":[237,257],"have":[239],"strongest":[241],"consistency":[242],"(PBMP),":[252],"shows":[255],"objectively":[260],"maps.":[266]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}