{"id":"https://openalex.org/W4312097393","doi":"https://doi.org/10.1109/cisp-bmei56279.2022.9980337","title":"Fitness Action Counting Based on MediaPipe","display_name":"Fitness Action Counting Based on MediaPipe","publication_year":2022,"publication_date":"2022-11-05","ids":{"openalex":"https://openalex.org/W4312097393","doi":"https://doi.org/10.1109/cisp-bmei56279.2022.9980337"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei56279.2022.9980337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei56279.2022.9980337","pdf_url":null,"source":{"id":"https://openalex.org/S4363605502","display_name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5101444957","display_name":"Xiangying Li","orcid":"https://orcid.org/0000-0003-3737-1342"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangying Li","raw_affiliation_strings":["Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100778616","display_name":"Mingwei Zhang","orcid":"https://orcid.org/0009-0006-7017-215X"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingwei Zhang","raw_affiliation_strings":["Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102439581","display_name":"Junnan Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junnan Gu","raw_affiliation_strings":["Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100749618","display_name":"Zhi Zhang","orcid":"https://orcid.org/0009-0000-5180-0452"},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zhang","raw_affiliation_strings":["Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Science and Technology, College of Computer Science and Technology,Wuhan,China,430065","institution_ids":["https://openalex.org/I43922553"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101444957"],"corresponding_institution_ids":["https://openalex.org/I43922553"],"apc_list":null,"apc_paid":null,"fwci":1.1978,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.86011693,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.998199999332428,"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":0.998199999332428,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9922999739646912,"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":0.9438999891281128,"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":0.7199621200561523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6006448268890381},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5400984287261963},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5311015248298645},{"id":"https://openalex.org/keywords/mainstream","display_name":"Mainstream","score":0.5132558345794678},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5082480311393738},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5029088854789734},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.47733670473098755},{"id":"https://openalex.org/keywords/fitness-test","display_name":"Fitness test","score":0.4404248595237732},{"id":"https://openalex.org/keywords/physical-fitness","display_name":"Physical fitness","score":0.34264522790908813},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.08374428749084473}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7199621200561523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6006448268890381},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5400984287261963},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5311015248298645},{"id":"https://openalex.org/C2777617010","wikidata":"https://www.wikidata.org/wiki/Q18957","display_name":"Mainstream","level":2,"score":0.5132558345794678},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5082480311393738},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5029088854789734},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.47733670473098755},{"id":"https://openalex.org/C2992185106","wikidata":"https://www.wikidata.org/wiki/Q604159","display_name":"Fitness test","level":3,"score":0.4404248595237732},{"id":"https://openalex.org/C171687745","wikidata":"https://www.wikidata.org/wiki/Q309252","display_name":"Physical fitness","level":2,"score":0.34264522790908813},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.08374428749084473},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei56279.2022.9980337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei56279.2022.9980337","pdf_url":null,"source":{"id":"https://openalex.org/S4363605502","display_name":"2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8818562682","display_name":null,"funder_award_id":"61673304","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2524851568","https://openalex.org/W2555554385","https://openalex.org/W2903831537","https://openalex.org/W2962730651","https://openalex.org/W2963265461","https://openalex.org/W2963781481","https://openalex.org/W3036422827","https://openalex.org/W3203199349","https://openalex.org/W4280618224","https://openalex.org/W4286224650","https://openalex.org/W4287755748","https://openalex.org/W4312900270","https://openalex.org/W6727548515","https://openalex.org/W6730734845","https://openalex.org/W6800331133","https://openalex.org/W6838339364"],"related_works":["https://openalex.org/W2768136631","https://openalex.org/W2085686992","https://openalex.org/W157213304","https://openalex.org/W2020116361","https://openalex.org/W3011944177","https://openalex.org/W2086915029","https://openalex.org/W52823932","https://openalex.org/W2038712625","https://openalex.org/W3044681751","https://openalex.org/W2393161498"],"abstract_inverted_index":{"AI":[0],"fitness":[1,16,23,32,48,64,102,112,166],"has":[2,144],"become":[3],"a":[4,41,62,152],"new":[5],"and":[6,21,28,45,73,75,82,99,110,120,139,151],"practical":[7],"way":[8],"of":[9,13,30,58,155],"fitness,":[10],"but":[11],"most":[12],"the":[14,26,76,87,105,111,125,130],"mainstream":[15,131],"apps":[17],"focus":[18],"on":[19,51,86,167],"guiding":[20],"planning":[22],"activities,":[24],"ignoring":[25],"detection":[27,70],"evaluation":[29],"users'":[31],"movements.":[33],"Aiming":[34],"at":[35],"this":[36,38],"phenomenon,":[37],"paper":[39],"proposed":[40],"method":[42,56],"to":[43,97],"classify":[44,100],"count":[46],"basic":[47],"movements":[49],"based":[50,85],"Google":[52],"Mediapipe":[53],"framework.":[54],"The":[55,116],"consists":[57],"three":[59],"steps:":[60],"First,":[61],"single":[63],"action":[65],"is":[66,158],"divided":[67],"into":[68],"two":[69],"states:":[71],"up":[72],"down,":[74],"corresponding":[77],"picture":[78],"samples":[79],"are":[80,108,114,122],"collected":[81],"trained.":[83],"Secondly,":[84],"generated":[88],"training":[89],"set":[90],"(csv":[91],"file),":[92],"KNN":[93],"algorithm":[94,143],"was":[95],"used":[96],"identify":[98],"different":[101],"actions.":[103],"Finally,":[104],"classification":[106],"results":[107],"processed":[109],"actions":[113],"counted.":[115],"best":[117],"recognition":[118,134,149],"angle":[119],"threshold":[121],"obtained":[123],"through":[124],"test":[126],"accuracy.":[127],"Compared":[128],"with":[129],"human":[132],"pose":[133],"frameworks":[135],"such":[136],"as":[137],"Openpose":[138],"Alphapose,":[140],"Mediapipe's":[141],"Blazepose":[142],"lower":[145],"performance":[146],"requirements,":[147],"faster":[148],"speed":[150],"high":[153],"level":[154],"accuracy,":[156],"which":[157],"more":[159],"suitable":[160],"for":[161,164],"personalized":[162],"needs":[163],"smart":[165],"mobile":[168],"devices":[169],"today.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7}],"updated_date":"2026-03-02T08:37:19.008085","created_date":"2025-10-10T00:00:00"}
