{"id":"https://openalex.org/W4317419445","doi":"https://doi.org/10.1109/gcce56475.2022.10014090","title":"Selective Use of Skeletal Information to Reduce Computational Complexity of Motion Matching","display_name":"Selective Use of Skeletal Information to Reduce Computational Complexity of Motion Matching","publication_year":2022,"publication_date":"2022-10-18","ids":{"openalex":"https://openalex.org/W4317419445","doi":"https://doi.org/10.1109/gcce56475.2022.10014090"},"language":"en","primary_location":{"id":"doi:10.1109/gcce56475.2022.10014090","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcce56475.2022.10014090","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th 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":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","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/A5023726722","display_name":"Shohei Adachi","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shohei Adachi","raw_affiliation_strings":["Waseda University,Graduate School of Fundamental Science and Engineering,Tokyo,Japan","Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Graduate School of Fundamental Science and Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041812077","display_name":"Ryohei Osawa","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryohei Osawa","raw_affiliation_strings":["Waseda University,Graduate School of Fundamental Science and Engineering,Tokyo,Japan","Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Graduate School of Fundamental Science and Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088389427","display_name":"Hiroshi Watanabe","orcid":"https://orcid.org/0000-0002-6742-1913"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Watanabe","raw_affiliation_strings":["Waseda University,Graduate School of Fundamental Science and Engineering,Tokyo,Japan","Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University,Graduate School of Fundamental Science and Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19010435,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"116","issue":null,"first_page":"68","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.996399998664856,"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":0.996399998664856,"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":0.9932000041007996,"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/T12290","display_name":"Human Motion and Animation","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8192346096038818},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6667042970657349},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6507200002670288},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5933959484100342},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5885226726531982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5121829509735107},{"id":"https://openalex.org/keywords/feature-matching","display_name":"Feature matching","score":0.4924663007259369},{"id":"https://openalex.org/keywords/execution-time","display_name":"Execution time","score":0.481847882270813},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4711911678314209},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4419505298137665},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.423020601272583},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3586307168006897},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32079657912254333},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.15260395407676697},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13961723446846008},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11368528008460999}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8192346096038818},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6667042970657349},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6507200002670288},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5933959484100342},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5885226726531982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5121829509735107},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.4924663007259369},{"id":"https://openalex.org/C2989134064","wikidata":"https://www.wikidata.org/wiki/Q288510","display_name":"Execution time","level":2,"score":0.481847882270813},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4711911678314209},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4419505298137665},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.423020601272583},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3586307168006897},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32079657912254333},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.15260395407676697},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13961723446846008},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11368528008460999},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/gcce56475.2022.10014090","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcce56475.2022.10014090","pdf_url":null,"source":{"id":"https://openalex.org/S4363607800","display_name":"2022 IEEE 11th 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":"2022 IEEE 11th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2078483536","https://openalex.org/W2559085405","https://openalex.org/W4239181501"],"related_works":["https://openalex.org/W2380016249","https://openalex.org/W1995188412","https://openalex.org/W2786306966","https://openalex.org/W2534909612","https://openalex.org/W1602226726","https://openalex.org/W2359993687","https://openalex.org/W3110752836","https://openalex.org/W3120997353","https://openalex.org/W3082415029","https://openalex.org/W2123144113"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,26,47,76],"improve":[3],"sports":[4],"skills,":[5],"the":[6,9,12,28,49,85,94,97,102,105,115,119,122],"comparison":[7],"of":[8,37,87,96,104,121],"movement":[10],"using":[11,23,54],"video":[13],"is":[14,58,74,90],"very":[15],"effective":[16,60],"for":[17,65,111],"progress.":[18],"Existing":[19],"studies":[20],"have":[21,34],"been":[22],"posture":[24],"similarity":[25],"map":[27],"motion":[29,113],"timing.":[30],"However,":[31],"these":[32],"methods":[33],"a":[35,38,45],"disadvantage":[36],"long":[39],"execution":[40,78],"time.":[41],"Therefore,":[42],"we":[43,70,100],"propose":[44],"method":[46],"reduce":[48,77],"computational":[50],"complexity":[51],"by":[52],"selectively":[53],"only":[55],"data":[56,63,89],"that":[57,72,117],"particularly":[59],"among":[61],"feature":[62,88],"used":[64],"mapping.":[66,123],"Through":[67],"evaluation":[68,98],"experiments,":[69],"confirm":[71],"it":[73],"possible":[75],"time":[79],"without":[80],"sacrificing":[81],"performance":[82],"even":[83],"when":[84],"number":[86],"reduced.":[91],"Based":[92],"on":[93],"results":[95],"experiment,":[99],"discuss":[101],"causes":[103],"increase":[106],"or":[107],"decrease":[108],"in":[109],"accuracy":[110,120],"each":[112],"and":[114],"factors":[116],"affect":[118]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}