{"id":"https://openalex.org/W2294932304","doi":"https://doi.org/10.1109/icmew.2015.7169778","title":"Feature-matching based motion prediction for high efficiency video coding in cloud","display_name":"Feature-matching based motion prediction for high efficiency video coding in cloud","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W2294932304","doi":"https://doi.org/10.1109/icmew.2015.7169778","mag":"2294932304"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2015.7169778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2015.7169778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Multimedia &amp; Expo Workshops (ICMEW)","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/A5100651136","display_name":"Xiang Zhang","orcid":"https://orcid.org/0000-0002-1017-742X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385178","display_name":"Shiqi Wang","orcid":"https://orcid.org/0000-0002-3583-959X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqi Wang","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385183","display_name":"Shanshe Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshe Wang","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039832462","display_name":"Siwei Ma","orcid":"https://orcid.org/0000-0002-2731-5403"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siwei Ma","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018478553","display_name":"Wen Gao","orcid":"https://orcid.org/0000-0002-8070-802X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Gao","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100651136"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.7994,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.80403316,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10531","display_name":"Advanced Vision and Imaging","score":0.9993000030517578,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9988999962806702,"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/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.8119791746139526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8014881610870361},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7743957042694092},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7341495156288147},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5524045825004578},{"id":"https://openalex.org/keywords/motion-vector","display_name":"Motion vector","score":0.5189146995544434},{"id":"https://openalex.org/keywords/motion-compensation","display_name":"Motion compensation","score":0.4776636064052582},{"id":"https://openalex.org/keywords/quarter-pixel-motion","display_name":"Quarter-pixel motion","score":0.46504226326942444},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4634893238544464},{"id":"https://openalex.org/keywords/multiview-video-coding","display_name":"Multiview Video Coding","score":0.4596289396286011},{"id":"https://openalex.org/keywords/algorithmic-efficiency","display_name":"Algorithmic efficiency","score":0.44996732473373413},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.4401299059391022},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42902541160583496},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.42179441452026367},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.42144694924354553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3754027783870697},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.22836196422576904},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.19658887386322021},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09852597117424011},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07841339707374573}],"concepts":[{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.8119791746139526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8014881610870361},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7743957042694092},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7341495156288147},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5524045825004578},{"id":"https://openalex.org/C2779020251","wikidata":"https://www.wikidata.org/wiki/Q3555171","display_name":"Motion vector","level":3,"score":0.5189146995544434},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.4776636064052582},{"id":"https://openalex.org/C174493125","wikidata":"https://www.wikidata.org/wiki/Q1073461","display_name":"Quarter-pixel motion","level":3,"score":0.46504226326942444},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4634893238544464},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.4596289396286011},{"id":"https://openalex.org/C116709606","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Algorithmic efficiency","level":3,"score":0.44996732473373413},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4401299059391022},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42902541160583496},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.42179441452026367},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.42144694924354553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3754027783870697},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.22836196422576904},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.19658887386322021},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09852597117424011},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07841339707374573},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2015.7169778","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2015.7169778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Multimedia &amp; Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1486316239","https://openalex.org/W1677409904","https://openalex.org/W1746112492","https://openalex.org/W1981758544","https://openalex.org/W1995967686","https://openalex.org/W2006002369","https://openalex.org/W2035754349","https://openalex.org/W2038677709","https://openalex.org/W2060658301","https://openalex.org/W2067445993","https://openalex.org/W2067732419","https://openalex.org/W2085261163","https://openalex.org/W2110513521","https://openalex.org/W2124386111","https://openalex.org/W2126130784","https://openalex.org/W2146395539","https://openalex.org/W2162530156","https://openalex.org/W6676679428"],"related_works":["https://openalex.org/W839483973","https://openalex.org/W2143589929","https://openalex.org/W4241657933","https://openalex.org/W1579940903","https://openalex.org/W2189223443","https://openalex.org/W3140103152","https://openalex.org/W2109074487","https://openalex.org/W2140821221","https://openalex.org/W2758567178","https://openalex.org/W4230504469"],"abstract_inverted_index":{"Visual":[0],"features":[1,31],"of":[2],"images":[3],"and":[4,10,21,35,62,100,122],"video":[5,81,109],"frames":[6],"have":[7,130],"become":[8],"pervasive":[9],"maturely":[11],"developed":[12],"in":[13,40,84,105],"extensive":[14],"research":[15],"fields":[16],"such":[17],"as":[18],"computer":[19],"vision":[20],"visual":[22,30],"search.":[23],"For":[24],"realtime":[25],"retrieval":[26],"applications,":[27],"the":[28,49,53,69,80,89,106,133,139,144],"compact":[29],"should":[32],"be":[33],"transmitted":[34],"stored":[36],"at":[37,119],"server":[38],"side":[39],"cloud.":[41],"These":[42],"local":[43],"feature":[44,72],"descriptors":[45],"are":[46],"characterized":[47],"by":[48,56,66],"invariance":[50],"properties":[51],"for":[52,97],"variances":[54],"caused":[55],"camera":[57],"motion,":[58],"illumination":[59],"changing,":[60],"occlusion":[61],"different":[63],"viewpoints.":[64],"Inspired":[65],"these":[67],"properties,":[68],"typical":[70],"scale-invariant":[71],"transform":[73],"(SIFT)":[74],"descriptor":[75],"is":[76,95,125],"leveraged":[77],"to":[78,143],"improve":[79,138],"coding":[82,110,140],"efficiency":[83,108],"this":[85],"work.":[86],"In":[87],"particular":[88],"predicted":[90],"motion":[91,101,115],"using":[92],"SIFT":[93],"matching":[94],"used":[96],"merge":[98],"mode":[99],"vector":[102],"prediction":[103],"(MVP)":[104],"high":[107],"(HEVC)":[111],"standard.":[112],"A":[113],"hierarchical":[114],"derivation":[116],"framework":[117],"aiming":[118],"achieving":[120],"robust":[121],"effective":[123],"MVP":[124],"further":[126],"proposed.":[127],"Experimental":[128],"results":[129],"shown":[131],"that":[132],"proposed":[134],"method":[135],"can":[136],"efficiently":[137],"performance":[141],"according":[142],"accurate":[145],"feature-matching.":[146]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
