{"id":"https://openalex.org/W2044692418","doi":"https://doi.org/10.1109/camad.1994.765629","title":"A markov-renewal-modulated tes model for jpeg-like compressed \"star wars\" video","display_name":"A markov-renewal-modulated tes model for jpeg-like compressed \"star wars\" video","publication_year":1994,"publication_date":"1994-01-01","ids":{"openalex":"https://openalex.org/W2044692418","doi":"https://doi.org/10.1109/camad.1994.765629","mag":"2044692418"},"language":"en","primary_location":{"id":"doi:10.1109/camad.1994.765629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camad.1994.765629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifth IEEE International Workshop on Computer-Aided Modeling, Analysis, and Design of Communication Links and Networks","raw_type":"proceedings-article"},"type":"conference-abstract","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/A5006668000","display_name":"Dimitrios Pendarakis","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"D. Pendarakis","raw_affiliation_strings":["Department of Electrical Engineering and CTR, Columbia University, NY, USA","Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and CTR, Columbia University, NY, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006668000"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"0_9","last_page":"0_9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.791700005531311,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11574","display_name":"Artificial Intelligence in Games","score":0.791700005531311,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.7799000144004822,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.7764999866485596,"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":0.5704984068870544},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.5594771504402161},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5208502411842346},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5181783437728882},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.46822378039360046},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.4551837146282196},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4298418462276459},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4266684651374817},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.337274968624115},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3013259172439575},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18556639552116394},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13879042863845825}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5704984068870544},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.5594771504402161},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5208502411842346},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5181783437728882},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.46822378039360046},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4551837146282196},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4298418462276459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4266684651374817},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.337274968624115},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3013259172439575},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18556639552116394},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13879042863845825},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/camad.1994.765629","is_oa":false,"landing_page_url":"https://doi.org/10.1109/camad.1994.765629","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifth IEEE International Workshop on Computer-Aided Modeling, Analysis, and Design of Communication Links and Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7200000286102295,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2084326697","https://openalex.org/W2027903142","https://openalex.org/W2354322608","https://openalex.org/W2804608325","https://openalex.org/W2077211377","https://openalex.org/W2413828414","https://openalex.org/W2186675474"],"abstract_inverted_index":{"The":[0,23,62,68,71,79,110,122,135,163,172,179,212,228,242,249,267,270,273],"Bulk":[1],"Of":[2,16,25,48,55,67,76,100,106,134,137,144,171,193,241,246,272,281,287,297,310,315],"Previous":[3],"Work":[4],"In":[5,115,178,263],"Video":[6,37,80],"Source":[7,285],"Modeling":[8,38,72,274],"Has":[9],"Been":[10],"Confined":[11],"To":[12,21,36,104,254,261],"Short":[13],"Se":[14,81],"Quences":[15],"Empirical":[17,26,69,164,256],"Records,":[18],"Which":[19,101],"Attempt":[20],"Capture":[22],"Autocorrelations":[24],"Bit":[27,95,243],"Rate":[28,244],"Records.":[29],"This":[30,116,305],"Talk":[31],"Presents":[32,45],"A":[33,46,49,118,141,150,184,218,236,279,313],"Novel":[34],"Approach":[35],"With":[39,223],"Two":[40],"Main":[41],"Contributions.":[42],"First,":[43],"It":[44,59],"Model":[47,152,160],"Full-length":[50],"Movie":[51,180,214],"(a":[52],"Jpeg-like":[53],"Version":[54],"\"star-wars\");":[56],"And":[57,64,147,168,258,276,283],"Second,":[58],"Captures":[60,162],"Both":[61],"Distribution":[63,166],"Autocorrelation":[65,169],"Functions":[66],"Record.":[70],"Methodology":[73,275,306],"Developed":[74,303],"Consists":[75,192],"Several":[77],"Stages.":[78],"Quence":[82],"Is":[83,102,124,153,215],"First":[84],"Segmented":[85],"Into":[86,97],"Scenes.":[87],"Individual":[88],"Scenes":[89],"Are":[90,181,201],"Then":[91],"Classified":[92],"(by":[93],"Mean":[94],"Rate)":[96],"Classes,":[98],"Each":[99,156,158,209],"Assumed":[103],"Consist":[105],"Sample":[107],"Realizations":[108],"From":[109],"Same":[111],"Probability":[112],"Law":[113],"-":[114],"Case":[117],"Tes":[119,151,159,220],"(transform-expand-sample)":[120],"Process.":[121],"Classification":[123],"Accomplished":[125],"Via":[126],"An":[127],"Iterative":[128],"Heuristic":[129],"Procedure":[130],"For":[131,155,208,291,307],"Partitional":[132],"Clustering":[133],"Set":[136,143],"Scenes,":[138],"Having":[139,234],"Identified":[140],"Suitable":[142,290],"Partitioning":[145],"Criteria":[146],"Parameters.":[148],"Next,":[149],"Derived":[154],"Class;":[157],"Simultaneously":[161],"Marginal":[165],"(histogram)":[167],"Function":[170],"Corresponding":[173],"Scene":[174,176,199],"Class.":[175,210],"Transitions":[177],"Modeled":[182,202,216],"As":[183,203,217],"Sim":[185],"Ple":[186],"Markov":[187],"Chain":[188],"Whose":[189],"State":[190],"Space":[191],"Just":[194],"Four":[195],"States":[196],"(scene":[197],"Classes).":[198],"Durations":[200],"Class-dependont":[204],"Renewal":[205],"Processes,":[206],"One":[207],"Thus,":[211],"Entire":[213],"Markov-renewal-modulated":[219],"(mrmt)":[221],"Process":[222,232,245],"Class-dependent":[224],"Holding":[225],"Times,":[226],"Generalizing":[227],"Well-known":[229],"Markov-modulated":[230],"Poisson":[231],"(mmpp).":[233],"Generated":[235],"\"synthetic\"":[237],"Monte":[238,294],"Carlo":[239,295],"Simulation":[240,250],"\"star":[247],"Wars\",":[248],"Statistics":[251],"Were":[252,259],"Compared":[253],"Their":[255],"Counterparts":[257],"Found":[260],"Be":[262,302],"General":[264],"Good":[265],"Agreement.":[266],"Results":[268],"Support":[269],"Efficacy":[271],"Suggest":[277],"That":[278],"Benchmark":[280],"Realistic":[282,293],"Compact":[284],"Models":[286],"Full-motion":[288],"Video,":[289],"Driving":[292],"Simulations":[296],"Broadband":[298],"Telecommunications":[299],"Networks,":[300],"Can":[301],"By":[304],"Other":[308],"Types":[309],"Movies":[311],"Under":[312],"Variety":[314],"Coding":[316],"Schemes.":[317]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}