{"id":"https://openalex.org/W2159584618","doi":"https://doi.org/10.1109/icip.2009.5414201","title":"Pre-fetching based on video analysis for interactive region-of-interest streaming of soccer sequences","display_name":"Pre-fetching based on video analysis for interactive region-of-interest streaming of soccer sequences","publication_year":2009,"publication_date":"2009-11-01","ids":{"openalex":"https://openalex.org/W2159584618","doi":"https://doi.org/10.1109/icip.2009.5414201","mag":"2159584618"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2009.5414201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5414201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","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/A5046104276","display_name":"Aditya Mavlankar","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aditya Mavlankar","raw_affiliation_strings":["Information Systems Laboratory, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Systems Laboratory, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004042863","display_name":"Bernd Girod","orcid":"https://orcid.org/0000-0001-6950-1020"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bernd Girod","raw_affiliation_strings":["Information Systems Laboratory, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Systems Laboratory, Department of Electrical Engineering, University of Stanford, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6424,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.86611404,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"5","issue":null,"first_page":"3061","last_page":"3064"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998999834060669,"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":0.9998999834060669,"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/T10741","display_name":"Video Coding and Compression Technologies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.998199999332428,"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":0.845716118812561},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.691193699836731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6288197040557861},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.6189963817596436},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5554887056350708},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5262443423271179},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.455043226480484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32546257972717285},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14977478981018066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1185716986656189}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.845716118812561},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.691193699836731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6288197040557861},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.6189963817596436},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5554887056350708},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5262443423271179},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.455043226480484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32546257972717285},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14977478981018066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1185716986656189},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2009.5414201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5414201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1552609016","https://openalex.org/W1558607066","https://openalex.org/W1571390362","https://openalex.org/W1604400733","https://openalex.org/W1645698388","https://openalex.org/W1967796019","https://openalex.org/W1978509032","https://openalex.org/W1980241600","https://openalex.org/W1995672495","https://openalex.org/W2120872315","https://openalex.org/W2124565395","https://openalex.org/W2124834956","https://openalex.org/W2150107408","https://openalex.org/W2153497304","https://openalex.org/W4240449172","https://openalex.org/W6633870039","https://openalex.org/W6677879816","https://openalex.org/W6822205141"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W2347897961","https://openalex.org/W2340870721","https://openalex.org/W2358318464","https://openalex.org/W2979236518","https://openalex.org/W3091955004"],"abstract_inverted_index":{"We":[0,44],"consider":[1],"a":[2,17,120,152,178],"video":[3,86],"streaming":[4,52],"system":[5],"in":[6,58],"which":[7],"the":[8,33,36,39,91,102,127,138,145,181],"user":[9],"can":[10,66,100,132,168],"interactively":[11],"watch":[12],"an":[13],"arbitrary":[14],"region":[15],"of":[16,27,41,72,90,124,129,155,165],"high-spatial-resolution":[18],"scene.":[19],"Region-of-interest":[20],"(RoI)":[21],"prediction":[22,35,50,112,122,161],"helps":[23],"pre-fetch":[24],"select":[25],"slices":[26],"encoded":[28],"video.":[29],"The":[30,88,163],"more":[31,105],"accurate":[32],"RoI":[34,49,104],"lower":[37],"is":[38,93,115],"percentage":[40,128,164],"missing":[42,130,166],"pixels.":[43],"compare":[45],"different":[46],"techniques":[47,56,78,99],"for":[48,51,80,110,119,137,144,159,176],"soccer":[53,81],"sequences.":[54],"Two":[55],"proposed":[57],"our":[59],"earlier":[60],"work":[61],"are":[62],"not":[63],"domain-specific":[64,98,147],"and":[65],"be":[67,133,169],"applied":[68],"to":[69,94,142,151],"any":[70],"type":[71],"content.":[73],"Here":[74],"we":[75],"propose":[76],"two":[77],"geared":[79],"sequences":[82],"that":[83,109],"perform":[84],"semantic":[85],"analysis.":[87],"goal":[89],"paper":[92],"find":[95],"out":[96],"whether":[97],"predict":[101],"client's":[103],"accurately.":[106],"Experiments":[107],"indicate":[108],"short":[111],"look-ahead":[113,123],"there":[114],"little":[116],"gain":[117,154],"whereas":[118],"long":[121,160],"2":[125],"seconds":[126],"pixels":[131,167],"reduced":[134,170],"from":[135],"24%":[136],"best":[139,146],"general":[140],"technique":[141],"18%":[143],"technique.":[148],"This":[149],"translates":[150],"PSNR":[153],"around":[156,180],"1":[157],"dB":[158],"look-ahead.":[162],"further":[171],"by":[172],"spending":[173],"additional":[174],"bitrate":[175],"pre-fetching":[177],"margin":[179],"predicted":[182],"RoI.":[183]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
