{"id":"https://openalex.org/W4200559076","doi":"https://doi.org/10.1109/gcce53005.2021.9621841","title":"Action Classification from Egocentric Videos Using Reinforcement Learning-based Pose Estimation","display_name":"Action Classification from Egocentric Videos Using Reinforcement Learning-based Pose Estimation","publication_year":2021,"publication_date":"2021-10-12","ids":{"openalex":"https://openalex.org/W4200559076","doi":"https://doi.org/10.1109/gcce53005.2021.9621841"},"language":"en","primary_location":{"id":"doi:10.1109/gcce53005.2021.9621841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621841","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","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/A5025529021","display_name":"Shunya Ohaga","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shunya Ohaga","raw_affiliation_strings":["School of Engineering, Hokkaido University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Hokkaido University, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002757875","display_name":"Ren Togo","orcid":"https://orcid.org/0000-0002-4474-3995"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ren Togo","raw_affiliation_strings":["Education and Research Center for Mathematical and Data Science, Hokkaido University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Education and Research Center for Mathematical and Data Science, Hokkaido University, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009032240","display_name":"Takahiro Ogawa","orcid":"https://orcid.org/0000-0001-5332-8112"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Ogawa","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"last","author":{"id":null,"display_name":"Miki Haseyama","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Miki Haseyama","raw_affiliation_strings":["Faculty of Information Science and Technology, Hokkaido University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Technology, Hokkaido University, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205349734"],"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":"9","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9921000003814697,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9801999926567078,"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/pose","display_name":"Pose","score":0.8351831436157227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7950074672698975},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7530403733253479},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6613782048225403},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.5707815885543823},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5615752339363098},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4793318510055542},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.47223329544067383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44255533814430237},{"id":"https://openalex.org/keywords/humanoid-robot","display_name":"Humanoid robot","score":0.42492252588272095},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42314955592155457},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15742141008377075},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.08249664306640625},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.07641622424125671}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8351831436157227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7950074672698975},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7530403733253479},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6613782048225403},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.5707815885543823},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5615752339363098},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4793318510055542},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.47223329544067383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44255533814430237},{"id":"https://openalex.org/C60692881","wikidata":"https://www.wikidata.org/wiki/Q584529","display_name":"Humanoid robot","level":3,"score":0.42492252588272095},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42314955592155457},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15742141008377075},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.08249664306640625},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.07641622424125671},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce53005.2021.9621841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621841","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1983364832","https://openalex.org/W2008056655","https://openalex.org/W2064675550","https://openalex.org/W2194775991","https://openalex.org/W2736601468","https://openalex.org/W2788865504","https://openalex.org/W2961193895","https://openalex.org/W2963015194","https://openalex.org/W2963524571","https://openalex.org/W2963782415","https://openalex.org/W3009150298","https://openalex.org/W3021013305","https://openalex.org/W3035367723","https://openalex.org/W3043142510","https://openalex.org/W3118589616","https://openalex.org/W6631190155","https://openalex.org/W6741002519","https://openalex.org/W6765307894","https://openalex.org/W6776730017"],"related_works":["https://openalex.org/W4297270893","https://openalex.org/W3135266094","https://openalex.org/W2577671007","https://openalex.org/W1591216093","https://openalex.org/W2912100719","https://openalex.org/W2963330455","https://openalex.org/W3091300685","https://openalex.org/W2331280411","https://openalex.org/W2952275251","https://openalex.org/W2783931899"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,80,104],"novel":[3],"action":[4,22,42,68,91,121],"classification":[5,23,43,69,92,122],"method":[6,116],"using":[7,84],"egocentric":[8,19,45,48,67,124],"pose":[9,25,39,54,64,81,100],"estimation":[10,26,40,82],"based":[11],"on":[12],"reinforcement":[13],"learning.":[14],"In":[15],"the":[16,62,72,98,114,120],"field":[17],"of":[18,75],"video":[20],"analysis,":[21],"and":[24,86],"have":[27,33],"actively":[28],"been":[29,34],"studied.":[30],"However,":[31],"there":[32],"few":[35],"works":[36],"that":[37,113],"use":[38],"for":[41,119],"from":[44,123],"videos.":[46,125],"Since":[47],"videos":[49],"do":[50],"not":[51],"contain":[52],"human":[53],"information,":[55],"it":[56],"will":[57],"be":[58],"effective":[59,118],"to":[60],"introduce":[61],"estimated":[63,99],"information":[65,102],"into":[66,103],"methods.":[70],"As":[71],"first":[73],"step":[74],"this":[76],"study,":[77],"we":[78],"train":[79],"model":[83,93],"flow":[85],"humanoid":[87],"information.":[88],"Then":[89],"an":[90],"is":[94,117],"trained":[95],"by":[96],"inputting":[97],"sequence":[101],"Bidirectional":[105],"Long":[106],"Short-Term":[107],"Memory":[108],"network.":[109],"Experimental":[110],"results":[111],"show":[112],"proposed":[115]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
