{"id":"https://openalex.org/W2343998578","doi":"https://doi.org/10.1109/vcip.2015.7457864","title":"Encoding scale into fisher vector for human action recognition","display_name":"Encoding scale into fisher vector for human action recognition","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2343998578","doi":"https://doi.org/10.1109/vcip.2015.7457864","mag":"2343998578"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2015.7457864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2015.7457864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100385142","display_name":"Bowen Zhang","orcid":"https://orcid.org/0000-0002-4971-4878"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Zhang","raw_affiliation_strings":["Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058982350","display_name":"Hanli Wang","orcid":"https://orcid.org/0000-0002-9999-4871"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanli Wang","raw_affiliation_strings":["Ministry of Education, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116953780"],"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":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/encoding","display_name":"Encoding (memory)","score":0.7608329057693481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6881654262542725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6844737529754639},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6602848768234253},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6480553150177002},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5842940807342529},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.5049052834510803},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.4799806773662567},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4527079463005066},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.45115578174591064},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32152095437049866},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16280412673950195},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.059342801570892334}],"concepts":[{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.7608329057693481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6881654262542725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6844737529754639},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6602848768234253},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6480553150177002},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5842940807342529},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.5049052834510803},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.4799806773662567},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4527079463005066},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.45115578174591064},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32152095437049866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16280412673950195},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.059342801570892334},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"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:10.1109/vcip.2015.7457864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2015.7457864","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Visual Communications and Image Processing (VCIP)","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":25,"referenced_works":["https://openalex.org/W1606858007","https://openalex.org/W1677409904","https://openalex.org/W1755205674","https://openalex.org/W1996904744","https://openalex.org/W2020163092","https://openalex.org/W2058537326","https://openalex.org/W2065249004","https://openalex.org/W2068611653","https://openalex.org/W2069682406","https://openalex.org/W2105101328","https://openalex.org/W2112328181","https://openalex.org/W2114361838","https://openalex.org/W2118877769","https://openalex.org/W2126579184","https://openalex.org/W2131042978","https://openalex.org/W2131846894","https://openalex.org/W2139594308","https://openalex.org/W2151103935","https://openalex.org/W2156303437","https://openalex.org/W2163292664","https://openalex.org/W6637400245","https://openalex.org/W6677137762","https://openalex.org/W6677548441","https://openalex.org/W6682864246","https://openalex.org/W6684114947"],"related_works":["https://openalex.org/W1975321310","https://openalex.org/W1952261593","https://openalex.org/W2014494654","https://openalex.org/W3130349901","https://openalex.org/W1579833936","https://openalex.org/W2107361128","https://openalex.org/W2095350775","https://openalex.org/W2990323019","https://openalex.org/W4235381733","https://openalex.org/W2014842417"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,80],"new":[4],"kind":[5],"of":[6,82,95,151],"Fisher":[7],"Vector":[8],"(FV)":[9],"model,":[10],"named":[11],"Scale":[12],"FV":[13,107,121,126],"(ScaleFV),":[14],"is":[15,39,87,91,128],"proposed":[16,31,153],"to":[17,43,51,130,146],"ameliorate":[18],"visual":[19,58],"feature":[20,33],"encoding":[21,57],"for":[22,32,137],"human":[23,138],"action":[24,139],"recognition.":[25,140],"Although":[26],"several":[27],"researches":[28],"have":[29],"been":[30],"encoding,":[34],"the":[35,44,60,96,106,112,148,152],"temporal":[36,61,83,99],"scale":[37,46,62,84,100,135],"information":[38,47,63,101,136],"almost":[40],"ignored.":[41],"Similar":[42],"spatial":[45,97],"which":[48],"has":[49],"shown":[50],"be":[52,103],"important":[53,67],"in":[54,69,85],"extracting":[55],"and":[56,89,98,134],"features,":[59],"also":[64],"plays":[65],"an":[66,119],"role":[68],"video":[70],"content":[71],"analysis":[72],"based":[73],"on":[74],"our":[75],"investigation.":[76],"To":[77],"demonstrate":[78,147],"this,":[79],"definition":[81],"videos":[86],"given,":[88],"it":[90],"presented":[92],"that":[93],"both":[94,132],"can":[102],"encoded":[104],"into":[105],"model":[108,122],"by":[109],"slightly":[110],"modifying":[111],"underlying":[113],"Gaussian":[114],"Mixture":[115],"Models":[116],"(GMM).":[117],"Furthermore,":[118],"enhanced":[120],"termed":[123],"as":[124],"Combined":[125],"(CombFV)":[127],"designed":[129],"capture":[131],"position":[133],"Comparative":[141],"experiments":[142],"are":[143],"carried":[144],"out":[145],"superior":[149],"performance":[150],"methods.":[154]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}