{"id":"https://openalex.org/W2972352920","doi":"https://doi.org/10.1109/lsp.2019.2940105","title":"A Risk-Aware Pairwise Rank Learning Approach for Visual Discomfort Prediction of Stereoscopic 3D","display_name":"A Risk-Aware Pairwise Rank Learning Approach for Visual Discomfort Prediction of Stereoscopic 3D","publication_year":2019,"publication_date":"2019-09-11","ids":{"openalex":"https://openalex.org/W2972352920","doi":"https://doi.org/10.1109/lsp.2019.2940105","mag":"2972352920"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2019.2940105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2940105","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5000581688","display_name":"Qiuping Jiang","orcid":"https://orcid.org/0000-0002-6025-9343"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiuping Jiang","raw_affiliation_strings":["School of Information Science and Engineering, Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049898953","display_name":"Feng Shao","orcid":"https://orcid.org/0000-0002-2495-9924"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Shao","raw_affiliation_strings":["School of Information Science and Engineering, Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050309466","display_name":"Wei Gao","orcid":"https://orcid.org/0000-0001-7429-5495"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Gao","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100339334","display_name":"Hong Li","orcid":"https://orcid.org/0000-0002-7400-7091"},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Li","raw_affiliation_strings":["College of Science and Technology, Ningbo University, Ningbo, China"],"affiliations":[{"raw_affiliation_string":"College of Science and Technology, Ningbo University, Ningbo, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061745929","display_name":"Yo\u2010Sung Ho","orcid":"https://orcid.org/0000-0002-7220-1034"},"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":"Yo-Sung Ho","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000581688"],"corresponding_institution_ids":["https://openalex.org/I109935558"],"apc_list":null,"apc_paid":null,"fwci":0.6073,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.72506988,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"26","issue":"11","first_page":"1588","last_page":"1592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"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":0.9998000264167786,"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":0.994700014591217,"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/T11408","display_name":"Advanced Optical Imaging Technologies","score":0.9939000010490417,"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/pairwise-comparison","display_name":"Pairwise comparison","score":0.8304784297943115},{"id":"https://openalex.org/keywords/stereoscopy","display_name":"Stereoscopy","score":0.7776488065719604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7551076412200928},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7112603187561035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.697821319103241},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5131202340126038},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5092371702194214},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4655616581439972},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.45984092354774475},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.43512314558029175},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43215489387512207},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.342735230922699},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11610040068626404},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09899061918258667}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.8304784297943115},{"id":"https://openalex.org/C126057942","wikidata":"https://www.wikidata.org/wiki/Q35158","display_name":"Stereoscopy","level":2,"score":0.7776488065719604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7551076412200928},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7112603187561035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.697821319103241},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5131202340126038},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5092371702194214},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4655616581439972},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.45984092354774475},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.43512314558029175},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43215489387512207},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.342735230922699},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11610040068626404},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09899061918258667},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2019.2940105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2940105","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2073421919","display_name":null,"funder_award_id":"61901236","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4397451791","display_name":null,"funder_award_id":"61801303","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G462245949","display_name":null,"funder_award_id":"61622109","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G498820307","display_name":null,"funder_award_id":"R18F010008","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1558079668","https://openalex.org/W1977246677","https://openalex.org/W1982471090","https://openalex.org/W1997247158","https://openalex.org/W2030294991","https://openalex.org/W2038094733","https://openalex.org/W2072441879","https://openalex.org/W2106276241","https://openalex.org/W2120823735","https://openalex.org/W2121513507","https://openalex.org/W2129644086","https://openalex.org/W2145725161","https://openalex.org/W2153635508","https://openalex.org/W2161907179","https://openalex.org/W2162692770","https://openalex.org/W2171349048","https://openalex.org/W2206823058","https://openalex.org/W2341145739","https://openalex.org/W2488089073","https://openalex.org/W2549557196","https://openalex.org/W2590402370","https://openalex.org/W2765934933","https://openalex.org/W2767658402","https://openalex.org/W2901376605"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2942366970","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2562400057","https://openalex.org/W1692008701","https://openalex.org/W2597588799","https://openalex.org/W4360593462","https://openalex.org/W2194570607"],"abstract_inverted_index":{"For":[0],"visual":[1,24,46],"discomfort":[2,25,47],"prediction":[3,105],"(VDP)":[4],"of":[5,21,146],"stereoscopic":[6,29,53],"3D":[7,54],"images,":[8],"a":[9,93,128,136],"common":[10],"two-stage":[11],"framework":[12,134],"is":[13],"to":[14,37,45,69,101],"first":[15],"extract":[16],"features":[17,44],"that":[18],"are":[19],"predictive":[20],"the":[22,39,42,58,85,104,108,142,154],"experienced":[23],"level":[26],"when":[27],"viewing":[28],"images":[30],"and":[31,73,144],"then":[32],"use":[33],"typical":[34],"regression":[35,114],"tools":[36,115],"learn":[38],"mapping":[40],"from":[41],"extracted":[43],"scores.":[48],"Most":[49],"existing":[50],"approaches":[51,111],"for":[52,116],"VDP":[55,110,149],"focus":[56],"on":[57,127],"former":[59],"stage,":[60],"i.e.,":[61],"feature":[62],"extraction,":[63],"while":[64],"limited":[65],"efforts":[66],"have":[67,140],"dedicated":[68],"exploiting":[70],"more":[71],"powerful":[72],"robust":[74],"learning":[75,133,155],"algorithms":[76],"in":[77],"this":[78,81,124],"field.":[79],"In":[80],"letter,":[82],"inspired":[83],"by":[84],"pairwise":[86,131],"comparison-based":[87],"subjective":[88],"evaluation":[89],"methodology,":[90],"we":[91],"propose":[92],"novel":[94],"Risk-Aware":[95],"Pairwise":[96],"Rank":[97],"Learning":[98],"(RAPRL)":[99],"approach":[100],"further":[102],"improve":[103],"accuracy.":[106],"Unlike":[107],"traditional":[109],"using":[112,151],"different":[113,130],"feature-score":[117],"mapping,":[118],"our":[119,147],"proposed":[120,148],"RARL":[121],"method":[122],"addresses":[123],"problem":[125],"based":[126],"completely":[129],"rank":[132],"with":[135],"risk-aware":[137],"constraint.":[138],"Experiments":[139],"verified":[141],"effectiveness":[143],"robustness":[145],"model":[150],"RAPRL":[152],"as":[153],"algorithm.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
