{"id":"https://openalex.org/W4386643066","doi":"https://doi.org/10.1145/3615452.3617939","title":"FAST: Fast and Accurate Adaptation in Live Video Analytics Using Intermediate Features","display_name":"FAST: Fast and Accurate Adaptation in Live Video Analytics Using Intermediate Features","publication_year":2023,"publication_date":"2023-09-12","ids":{"openalex":"https://openalex.org/W4386643066","doi":"https://doi.org/10.1145/3615452.3617939"},"language":"en","primary_location":{"id":"doi:10.1145/3615452.3617939","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615452.3617939","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615452.3617939","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM Workshop on Mobile Immersive Computing, Networking, and Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3615452.3617939","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026620450","display_name":"S. H. Shin","orcid":"https://orcid.org/0009-0008-6074-3611"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seokgyeong Shin","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009621491","display_name":"Juheon Yi","orcid":"https://orcid.org/0000-0002-5080-7502"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Juheon Yi","raw_affiliation_strings":["Seoul National University, Seoul, Korea, South ? Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Korea, South ? Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064228159","display_name":"Minkyung Jeong","orcid":"https://orcid.org/0009-0006-5707-8134"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minkyung Jeong","raw_affiliation_strings":["Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114626700","display_name":"Youngki Lee","orcid":"https://orcid.org/0000-0002-1319-7071"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngki Lee","raw_affiliation_strings":["Seoul National University, Seoul, Korea, South ? Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Seoul, Korea, South ? Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5026620450"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1073554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"208","last_page":"214"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9977999925613403,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8338192701339722},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.773737370967865},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7325336933135986},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6837142705917358},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.5174839496612549},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5081257820129395},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.492575466632843},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43881362676620483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40006113052368164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35793042182922363},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24349871277809143}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8338192701339722},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.773737370967865},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7325336933135986},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6837142705917358},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.5174839496612549},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5081257820129395},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.492575466632843},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43881362676620483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40006113052368164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35793042182922363},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24349871277809143},{"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3615452.3617939","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615452.3617939","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615452.3617939","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM Workshop on Mobile Immersive Computing, Networking, and Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3615452.3617939","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3615452.3617939","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3615452.3617939","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM Workshop on Mobile Immersive Computing, Networking, and Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2057981749","display_name":null,"funder_award_id":"2022R1A2C3008495","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G3034753964","display_name":null,"funder_award_id":"grant","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G342704958","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G3510917025","display_name":null,"funder_award_id":"2022R1","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386643066.pdf","grobid_xml":"https://content.openalex.org/works/W4386643066.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2028045978","https://openalex.org/W2169393322","https://openalex.org/W2520509592","https://openalex.org/W2766766681","https://openalex.org/W2872933037","https://openalex.org/W2887117815","https://openalex.org/W2949520286","https://openalex.org/W2962851944","https://openalex.org/W2965289829","https://openalex.org/W2987144427","https://openalex.org/W3022536434","https://openalex.org/W3026990304","https://openalex.org/W3034971973","https://openalex.org/W3046256272","https://openalex.org/W3046754651","https://openalex.org/W3088076788","https://openalex.org/W3107875635","https://openalex.org/W4220738176","https://openalex.org/W4224066359","https://openalex.org/W4225096170","https://openalex.org/W4283204165","https://openalex.org/W4288327876","https://openalex.org/W6810496073"],"related_works":["https://openalex.org/W2997567050","https://openalex.org/W1483272040","https://openalex.org/W4283377908","https://openalex.org/W1533421371","https://openalex.org/W2003050223","https://openalex.org/W2787993192","https://openalex.org/W2091777911","https://openalex.org/W2766405861","https://openalex.org/W2360975119","https://openalex.org/W2912421143"],"abstract_inverted_index":{"Live":[0],"video":[1,49],"analytics":[2],"need":[3],"to":[4,9,28,75,80,100,113,126],"adapt":[5],"the":[6,11,24,29,59,63,77,85,102,105],"optimal":[7],"configuration":[8],"achieve":[10],"requirements":[12],"for":[13,20,42,91],"various":[14],"videos":[15],"of":[16,54,62,104],"environments.":[17],"Prior":[18],"works":[19],"adaptation":[21,46,69],"suffer":[22],"from":[23],"accuracy":[25,124],"drop":[26],"due":[27],"large":[30],"overhead":[31],"and":[32,44,70,83,97,120],"incorrect":[33],"estimation.":[34],"We":[35,87],"present":[36],"FAST,":[37],"a":[38],"Feature-based":[39],"Adaptation":[40],"SysTem,":[41],"immediate":[43],"accurate":[45],"in":[47],"live":[48],"analytics.":[50],"To":[51],"overcome":[52],"limitations":[53],"prior":[55],"works,":[56],"we":[57],"leverage":[58],"intermediate":[60,106],"feature":[61],"task.":[64],"Intermediate":[65],"features":[66],"enable":[67],"fine-grained":[68],"ambiguity":[71],"distinction,":[72],"which":[73],"leads":[74],"reducing":[76],"frame":[78,118],"size":[79,119],"be":[81],"transmitted":[82],"increasing":[84],"accuracy.":[86],"design":[88],"end-to-end":[89],"systems":[90],"two":[92],"representative":[93],"tasks":[94],"(object":[95],"detection":[96],"heartrate":[98],"measurement)":[99],"verify":[101],"benefits":[103],"features.":[107],"Evaluations":[108],"show":[109],"FAST":[110],"achieves":[111],"up":[112],"6.95":[114],"x":[115,122],"lower":[116],"average":[117],"2.69":[121],"higher":[123],"compared":[125],"state-of-the-art":[127],"adaptation.":[128]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
