{"id":"https://openalex.org/W4308235827","doi":"https://doi.org/10.1109/icip46576.2022.9897602","title":"Clustering-Based Psychometric No-Reference Quality Model for Point Cloud Video","display_name":"Clustering-Based Psychometric No-Reference Quality Model for Point Cloud Video","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308235827","doi":"https://doi.org/10.1109/icip46576.2022.9897602"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897602","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://biblio.ugent.be/publication/8770989/file/8770991.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073712882","display_name":"Sam Van Damme","orcid":"https://orcid.org/0000-0001-5398-7927"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I196972281","display_name":"Imec the Netherlands","ror":"https://ror.org/01ezq2j76","country_code":"NL","type":"facility","lineage":["https://openalex.org/I196972281"]}],"countries":["BE","NL"],"is_corresponding":true,"raw_author_name":"Sam Van Damme","raw_affiliation_strings":["Ghent University - imec,IDLab,Department of Information Technology (INTEC)","Department of Information Technology (INTEC), IDLab, Ghent University - imec"],"affiliations":[{"raw_affiliation_string":"Ghent University - imec,IDLab,Department of Information Technology (INTEC)","institution_ids":["https://openalex.org/I196972281","https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Information Technology (INTEC), IDLab, Ghent University - imec","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044425124","display_name":"Maria Torres Vega","orcid":"https://orcid.org/0000-0002-5656-6607"},"institutions":[{"id":"https://openalex.org/I196972281","display_name":"Imec the Netherlands","ror":"https://ror.org/01ezq2j76","country_code":"NL","type":"facility","lineage":["https://openalex.org/I196972281"]},{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE","NL"],"is_corresponding":false,"raw_author_name":"Maria Torres Vega","raw_affiliation_strings":["Ghent University - imec,IDLab,Department of Information Technology (INTEC)","Department of Information Technology (INTEC), IDLab, Ghent University - imec"],"affiliations":[{"raw_affiliation_string":"Ghent University - imec,IDLab,Department of Information Technology (INTEC)","institution_ids":["https://openalex.org/I196972281","https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Information Technology (INTEC), IDLab, Ghent University - imec","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010214320","display_name":"Jeroen van der Hooft","orcid":"https://orcid.org/0000-0002-9416-9661"},"institutions":[{"id":"https://openalex.org/I196972281","display_name":"Imec the Netherlands","ror":"https://ror.org/01ezq2j76","country_code":"NL","type":"facility","lineage":["https://openalex.org/I196972281"]},{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE","NL"],"is_corresponding":false,"raw_author_name":"Jeroen van der Hooft","raw_affiliation_strings":["Ghent University - imec,IDLab,Department of Information Technology (INTEC)","Department of Information Technology (INTEC), IDLab, Ghent University - imec"],"affiliations":[{"raw_affiliation_string":"Ghent University - imec,IDLab,Department of Information Technology (INTEC)","institution_ids":["https://openalex.org/I196972281","https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Information Technology (INTEC), IDLab, Ghent University - imec","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051784384","display_name":"Filip De Turck","orcid":"https://orcid.org/0000-0003-4824-1199"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]},{"id":"https://openalex.org/I196972281","display_name":"Imec the Netherlands","ror":"https://ror.org/01ezq2j76","country_code":"NL","type":"facility","lineage":["https://openalex.org/I196972281"]}],"countries":["BE","NL"],"is_corresponding":false,"raw_author_name":"Filip De Turck","raw_affiliation_strings":["Ghent University - imec,IDLab,Department of Information Technology (INTEC)","Department of Information Technology (INTEC), IDLab, Ghent University - imec"],"affiliations":[{"raw_affiliation_string":"Ghent University - imec,IDLab,Department of Information Technology (INTEC)","institution_ids":["https://openalex.org/I196972281","https://openalex.org/I32597200"]},{"raw_affiliation_string":"Department of Information Technology (INTEC), IDLab, Ghent University - imec","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073712882"],"corresponding_institution_ids":["https://openalex.org/I196972281","https://openalex.org/I32597200"],"apc_list":null,"apc_paid":null,"fwci":0.6566,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78343859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1866","last_page":"1870"},"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/T10648","display_name":"Virtual Reality Applications and Impacts","score":0.9731000065803528,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9470999836921692,"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/computer-science","display_name":"Computer science","score":0.8443534970283508},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6954913139343262},{"id":"https://openalex.org/keywords/quality-of-experience","display_name":"Quality of experience","score":0.6315925121307373},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5944156050682068},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5933594107627869},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.5580222010612488},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5463630557060242},{"id":"https://openalex.org/keywords/subjective-video-quality","display_name":"Subjective video quality","score":0.5194127559661865},{"id":"https://openalex.org/keywords/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.4398975074291229},{"id":"https://openalex.org/keywords/quality-of-service","display_name":"Quality of service","score":0.43608468770980835},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41776132583618164},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4047328233718872},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34695714712142944},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.34237635135650635},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.340520977973938},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.22357946634292603},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15169605612754822},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12038394808769226},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.10128873586654663},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09836670756340027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8443534970283508},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6954913139343262},{"id":"https://openalex.org/C2779333187","wikidata":"https://www.wikidata.org/wiki/Q3132648","display_name":"Quality of experience","level":3,"score":0.6315925121307373},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5944156050682068},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5933594107627869},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.5580222010612488},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5463630557060242},{"id":"https://openalex.org/C114227958","wikidata":"https://www.wikidata.org/wiki/Q7631422","display_name":"Subjective video quality","level":4,"score":0.5194127559661865},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.4398975074291229},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.43608468770980835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41776132583618164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4047328233718872},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34695714712142944},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.34237635135650635},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.340520977973938},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.22357946634292603},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15169605612754822},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12038394808769226},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.10128873586654663},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09836670756340027},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip46576.2022.9897602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897602","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:archive.ugent.be:8770989","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-8770989","pdf_url":"https://biblio.ugent.be/publication/8770989/file/8770991.pdf","source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9781665496209","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:archive.ugent.be:8770989","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-8770989","pdf_url":"https://biblio.ugent.be/publication/8770989/file/8770991.pdf","source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9781665496209","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5827440779","display_name":null,"funder_award_id":"1281021N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G6103319188","display_name":null,"funder_award_id":"1SB1822N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G866546231","display_name":null,"funder_award_id":"12W4819N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320327336","display_name":"Vlaamse regering","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4308235827.pdf","grobid_xml":"https://content.openalex.org/works/W4308235827.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1967464378","https://openalex.org/W2022359415","https://openalex.org/W2125654704","https://openalex.org/W2133665775","https://openalex.org/W2236395554","https://openalex.org/W2296530527","https://openalex.org/W2460795006","https://openalex.org/W3016718200","https://openalex.org/W3036519337","https://openalex.org/W3037320139","https://openalex.org/W3044529335","https://openalex.org/W3089343273","https://openalex.org/W3094394107","https://openalex.org/W3096788322","https://openalex.org/W3172963178","https://openalex.org/W3177112295","https://openalex.org/W6719073361"],"related_works":["https://openalex.org/W4388138958","https://openalex.org/W1996919562","https://openalex.org/W2883239366","https://openalex.org/W4390768785","https://openalex.org/W1971541619","https://openalex.org/W3127182254","https://openalex.org/W1543922763","https://openalex.org/W1999662728","https://openalex.org/W2053916852","https://openalex.org/W2796797126"],"abstract_inverted_index":{"Point":[0],"cloud":[1,129,188],"video":[2],"streaming":[3,186],"is":[4,67,89],"a":[5,90,120,157,175],"fundamental":[6],"application":[7],"of":[8,17,31,54,63,133,191],"immersive":[9],"multimedia.":[10],"In":[11,115],"it,":[12],"objects":[13],"represented":[14],"as":[15,57,59],"sets":[16],"points":[18],"are":[19,72,100],"streamed":[20],"and":[21,83,138,148,164,195],"displayed":[22],"to":[23,79,103,112,156,172],"remote":[24],"users.":[25],"Given":[26],"the":[27,37,43,52,55,105,150],"high":[28,153],"bandwidth":[29],"requirements":[30],"this":[32,116],"content,":[33],"small":[34],"changes":[35],"in":[36,47,75,198],"network":[38],"and/or":[39],"encoding":[40],"can":[41],"affect":[42],"users'":[44],"perceived":[45],"quality":[46,87],"unexpected":[48],"manners.":[49],"To":[50],"tackle":[51],"degradation":[53],"service":[56],"fast":[58],"possible,":[60],"real-time":[61],"Quality":[62],"Experience":[64],"(QoE)":[65],"assessment":[66,88,125],"needed.":[68],"As":[69],"subjective":[70],"evaluations":[71],"not":[73],"feasible":[74],"real":[76],"time":[77],"due":[78],"their":[80],"inherent":[81],"costs":[82],"duration,":[84],"low-complexity":[85],"objective":[86,95,122,179],"must.":[91],"Traditional":[92],"No-Reference":[93],"(NR)":[94],"metrics":[96],"at":[97],"client":[98],"side":[99],"best":[101],"suited":[102],"fulfill":[104],"task.":[106],"However,":[107],"they":[108],"lack":[109],"on":[110,174,183],"accuracy":[111],"human":[113],"perception.":[114],"paper,":[117],"we":[118],"present":[119],"cluster-based":[121],"NR":[123,143],"QoE":[124],"model":[126,151],"for":[127],"point":[128,187],"video.":[130],"By":[131],"means":[132],"Machine":[134],"Learning":[135],"(ML)-based":[136],"clustering":[137],"prediction":[139],"techniques":[140],"combined":[141],"with":[142],"pixel-based":[144],"features":[145],"(e.g.,":[146],"blur":[147],"noise),":[149],"shows":[152],"correlations":[154],"(up":[155],"0.977":[158],"Pearson":[159],"Linear":[160],"Correlation":[161],"Coefficient":[162],"(PLCC))":[163],"low":[165],"Root":[166],"Mean":[167],"Squared":[168],"Error":[169],"(RMSE)":[170],"(down":[171],"0.077":[173],"zero-to-one":[176],"scale)":[177],"towards":[178],"benchmarks":[180],"after":[181],"evaluation":[182],"an":[184],"adaptive":[185],"dataset":[189],"consisting":[190],"sixteen":[192],"source":[193],"videos":[194],"453":[196],"sequences":[197],"total.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
