{"id":"https://openalex.org/W4244556879","doi":"https://doi.org/10.1109/mmsp53017.2021.9733489","title":"Deep Learning-based Semantic Analysis of Sparse Light Field Ray Sets","display_name":"Deep Learning-based Semantic Analysis of Sparse Light Field Ray Sets","publication_year":2021,"publication_date":"2021-10-06","ids":{"openalex":"https://openalex.org/W4244556879","doi":"https://doi.org/10.1109/mmsp53017.2021.9733489"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp53017.2021.9733489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp53017.2021.9733489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)","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/A5055067018","display_name":"Kelvin Chelli","orcid":null},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Kelvin Chelli","raw_affiliation_strings":["Saarland Informatics Campus,Saarbr&#x00FC;cken,Germany,D-66123"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saarland Informatics Campus,Saarbr&#x00FC;cken,Germany,D-66123","institution_ids":["https://openalex.org/I91712215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060303910","display_name":"Roopak R. Tamboli","orcid":"https://orcid.org/0000-0002-5123-6422"},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Roopak R. Tamboli","raw_affiliation_strings":["Saarland Informatics Campus,Saarbr&#x00FC;cken,Germany,D-66123"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saarland Informatics Campus,Saarbr&#x00FC;cken,Germany,D-66123","institution_ids":["https://openalex.org/I91712215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025754162","display_name":"Thorsten Herfet","orcid":"https://orcid.org/0000-0002-3746-7638"},"institutions":[{"id":"https://openalex.org/I91712215","display_name":"Saarland University","ror":"https://ror.org/01jdpyv68","country_code":"DE","type":"education","lineage":["https://openalex.org/I91712215"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thorsten Herfet","raw_affiliation_strings":["Saarland Informatics Campus,Saarbr&#x00FC;cken,Germany,D-66123"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saarland Informatics Campus,Saarbr&#x00FC;cken,Germany,D-66123","institution_ids":["https://openalex.org/I91712215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20083547,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.996999979019165,"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/T11019","display_name":"Image Enhancement Techniques","score":0.996999979019165,"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":0.9969000220298767,"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/T11666","display_name":"Color Science and Applications","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8201936483383179},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6827939748764038},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6485904455184937},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4849667549133301},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4754055440425873},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.47486281394958496},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45854806900024414},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4250376224517822}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8201936483383179},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6827939748764038},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6485904455184937},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4849667549133301},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4754055440425873},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.47486281394958496},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45854806900024414},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4250376224517822},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmsp53017.2021.9733489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp53017.2021.9733489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2128268941","https://openalex.org/W2133665775","https://openalex.org/W2523246573","https://openalex.org/W2591697814","https://openalex.org/W2735920098","https://openalex.org/W2737842117","https://openalex.org/W2773172460","https://openalex.org/W2784129942","https://openalex.org/W2798270832","https://openalex.org/W2891331657","https://openalex.org/W2912212100","https://openalex.org/W2982579843","https://openalex.org/W2998657805","https://openalex.org/W3011008323","https://openalex.org/W3015843361","https://openalex.org/W3033268813","https://openalex.org/W3058004543","https://openalex.org/W3110151525","https://openalex.org/W3154072527","https://openalex.org/W3160276755","https://openalex.org/W4297779039","https://openalex.org/W6727249380","https://openalex.org/W6734447043","https://openalex.org/W6755310813"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W4375867731","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1977636359","https://openalex.org/W2772305933"],"abstract_inverted_index":{"With":[0],"the":[1,26,31,51,106,118,124,128,141,145,193,197,208,219,227,231],"emergence":[2],"of":[3,11,34,53,81,86,89,113,120,127,151,159,171,212,221,230],"various":[4,58],"light":[5],"field":[6],"(LF)":[7],"acquisition":[8],"systems":[9,21],"and":[10,16,47,49,97,99,109,134,137,190],"novel":[12],"techniques":[13,122],"for":[14,25],"processing":[15,43,112],"visualizing":[17],"LFs,":[18],"end-to-end":[19],"LF":[20,42,54,76,198,232],"start":[22],"to":[23,72,176,182,207],"head":[24],"consumer":[27],"market.":[28],"Towards":[29],"this,":[30],"semantic":[32,102,111],"analysis":[33,103,150,170,211],"LFs":[35],"can":[36,217],"play":[37],"a":[38,70,84,87,154,178,214],"crucial":[39],"role":[40],"in":[41,50,91,140,157,164],"(e.g.":[44,130],"compression,":[45],"storage":[46],"transmission),":[48],"standardization":[52],"representation":[55],"schemes":[56],"across":[57],"use":[59,177],"cases.":[60],"In":[61],"this":[62,165],"regard,":[63],"we":[64,167,174],"earlier":[65,146],"have":[66],"introduced":[67],"fristograms":[68,116],"as":[69,187,233],"tool":[71],"integrate":[73],"semantics":[74],"into":[75],"processing.":[77],"Fristograms":[78],"collect":[79],"sets":[80],"rays":[82,160,222],"within":[83],"volume":[85],"number":[88,158,220],"pixels":[90],"all":[92],"3":[93],"directions":[94],"(horizontal,":[95],"vertical":[96],"disparity)":[98],"thus":[100],"enable":[101,117],"based":[104],"on":[105],"ray":[107,210],"sets,":[108],"consequently":[110],"LFs.":[114],"Consequently,":[115],"application":[119],"filtering":[121],"considering":[123],"underlying":[125],"characteristic":[126],"scene":[129],"differentiate":[131],"between":[132],"Lambertian":[133],"non-Lambertian,":[135,189],"occluded":[136],"dis-occluded":[138],"regions":[139],"scene).":[142],"Motivated":[143],"by":[144,235],"results":[147,203],"through":[148],"statistical":[149,209],"froxels":[152],"enabling":[153],"significant":[155],"reduction":[156],"while":[161],"maintaining":[162],"quality,":[163],"paper,":[166],"explore":[168],"learning-based":[169,215],"froxels.":[172],"Specifically,":[173],"propose":[175],"deep":[179],"learning":[180],"network":[181],"classify":[183],"material":[184],"properties":[185],"(such":[186],"Lambertian,":[188],"outliers).":[191],"Once":[192],"classification":[194],"is":[195,199],"done,":[196],"filtered":[200],"semantically.":[201],"Preliminary":[202],"show":[204],"that":[205],"compared":[206],"froxels,":[213],"approach":[216],"reduce":[218],"even":[223],"further,":[224],"yet":[225],"maintain":[226],"visual":[228],"quality":[229,237],"measured":[234],"well-known":[236],"metrics.":[238]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
