{"id":"https://openalex.org/W1968953999","doi":"https://doi.org/10.1109/pcs.2013.6737753","title":"Joint decoding of independently encoded compressive multi-view video streams","display_name":"Joint decoding of independently encoded compressive multi-view video streams","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W1968953999","doi":"https://doi.org/10.1109/pcs.2013.6737753","mag":"1968953999"},"language":"en","primary_location":{"id":"doi:10.1109/pcs.2013.6737753","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2013.6737753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Picture Coding Symposium (PCS)","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/A5045555078","display_name":"Nan Cen","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nan Cen","raw_affiliation_strings":["Department of Electrical Engineering, The State University of New York (SUNY) at Buffalo, Buffalo, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The State University of New York (SUNY) at Buffalo, Buffalo, NY","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085416965","display_name":"Zhangyu Guan","orcid":"https://orcid.org/0000-0001-6134-215X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangyu Guan","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054337759","display_name":"Tommaso Melodia","orcid":"https://orcid.org/0000-0002-2719-1789"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tommaso Melodia","raw_affiliation_strings":["Department of Electrical Engineering, The State University of New York (SUNY) at Buffalo, Buffalo, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The State University of New York (SUNY) at Buffalo, Buffalo, NY","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4109,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.7977305,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"7744","issue":null,"first_page":"341","last_page":"344"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.8247324228286743},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8033356666564941},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.657275915145874},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5752135515213013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5169026851654053},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4900325536727905},{"id":"https://openalex.org/keywords/video-quality","display_name":"Video quality","score":0.44735467433929443},{"id":"https://openalex.org/keywords/multiview-video-coding","display_name":"Multiview Video Coding","score":0.44730186462402344},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4468723237514496},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4389183521270752},{"id":"https://openalex.org/keywords/motion-compensation","display_name":"Motion compensation","score":0.4292933940887451},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.42852717638015747},{"id":"https://openalex.org/keywords/motion-vector","display_name":"Motion vector","score":0.4204343557357788},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27984464168548584},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.22506797313690186},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.21980801224708557},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12810662388801575},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11612007021903992}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8247324228286743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8033356666564941},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.657275915145874},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5752135515213013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5169026851654053},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4900325536727905},{"id":"https://openalex.org/C103910844","wikidata":"https://www.wikidata.org/wiki/Q2631256","display_name":"Video quality","level":3,"score":0.44735467433929443},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.44730186462402344},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4468723237514496},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4389183521270752},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.4292933940887451},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.42852717638015747},{"id":"https://openalex.org/C2779020251","wikidata":"https://www.wikidata.org/wiki/Q3555171","display_name":"Motion vector","level":3,"score":0.4204343557357788},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27984464168548584},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.22506797313690186},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.21980801224708557},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12810662388801575},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11612007021903992},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"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/pcs.2013.6737753","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2013.6737753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.434.9471","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.434.9471","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.eng.buffalo.edu/wnesl/papers/NancyPCS2013.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W178701193","https://openalex.org/W1974358662","https://openalex.org/W2013452464","https://openalex.org/W2040744919","https://openalex.org/W2067743803","https://openalex.org/W2097213486","https://openalex.org/W2097751785","https://openalex.org/W2099213070","https://openalex.org/W2109449402","https://openalex.org/W2110044262","https://openalex.org/W2119667497","https://openalex.org/W2123033018","https://openalex.org/W2130003075","https://openalex.org/W2133665775","https://openalex.org/W2150412388","https://openalex.org/W2296616510","https://openalex.org/W4250955649","https://openalex.org/W6653333610","https://openalex.org/W6675069401","https://openalex.org/W6679250705"],"related_works":["https://openalex.org/W4285350705","https://openalex.org/W2548747278","https://openalex.org/W1579940903","https://openalex.org/W2358300437","https://openalex.org/W2762916849","https://openalex.org/W3161024829","https://openalex.org/W1988704969","https://openalex.org/W2187171999","https://openalex.org/W4247116801","https://openalex.org/W2366349316"],"abstract_inverted_index":{"We":[0,31,164,192],"design":[1,182],"a":[2,34,65,86,154,167],"video":[3,10,29,76,169,190,201],"coding":[4],"and":[5,83,116,118],"decoding":[6,23,46,226],"framework":[7,180],"for":[8,67,187],"multi-view":[9,28,189,200],"systems":[11],"based":[12],"on":[13,21],"compressed":[14],"sensing":[15],"imaging":[16],"principles.":[17],"Specifically,":[18],"we":[19,56,100],"focus":[20],"joint":[22,45],"of":[24,47,78,92,131,213,227],"independently":[25],"encoded":[26,82],"compressively-sampled":[27,50],"streams.":[30],"first":[32],"propose":[33,166],"novel":[35],"distributed":[36],"coding/decoding":[37],"architecture":[38],"designed":[39,156],"to":[40,61,72,104,127,148,181,207],"leverage":[41],"inter-view":[42,133],"correlation":[43],"through":[44,153],"the":[48,53,68,79,93,97,106,122,132,144,150,161,178,195,219],"received":[49],"frames.":[51,229],"At":[52,96],"encoder":[54],"side,":[55,99],"select":[57],"one":[58],"view":[59],"(referred":[60,71],"as":[62,64,73,108],"K-view)":[63],"reference":[66],"other":[69],"views":[70],"CS-views).":[74],"The":[75,136],"frames":[77],"CS-view":[80,125,138,151],"are":[81,140],"transmitted":[84],"at":[85],"lower":[87],"measurement":[88,162],"rate":[89,184],"than":[90],"those":[91],"selected":[94],"K-view.":[95],"decoder":[98],"generate":[101],"side":[102,146],"information":[103],"decode":[105],"CS-views":[107],"follows.":[109],"First,":[110],"each":[111],"K-view":[112],"frame":[113,126,152],"is":[114],"down-sampled":[115],"reconstructed,":[117],"then":[119,141],"compared":[120,222],"with":[121,143,223],"initially":[123],"reconstructed":[124],"obtain":[128],"an":[129],"estimate":[130],"motion":[134],"vector.":[135],"original":[137],"measurements":[139],"fused":[142],"generated":[145],"image":[147],"reconstruct":[149],"newly":[155],"algorithm":[157],"that":[158,173,205],"operates":[159],"in":[160,211],"domain.":[163],"also":[165],"blind":[168],"quality":[170],"estimation":[171],"method":[172],"can":[174,215],"be":[175,216],"used":[176],"within":[177],"proposed":[179,196,220],"channel-adaptive":[183],"control":[185],"algorithms":[186],"quality-assured":[188],"streaming.":[191],"extensively":[193],"evaluate":[194],"scheme":[197,221],"using":[198],"real":[199],"traces.":[202],"Results":[203],"indicate":[204],"up":[206],"1.6":[208],"dB":[209],"improvement":[210],"terms":[212],"PSNR":[214],"achieved":[217],"by":[218],"traditional":[224],"independent":[225],"CS":[228]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}