{"id":"https://openalex.org/W2065502920","doi":"https://doi.org/10.1109/icapr.2015.7050706","title":"Human action recognition based on motion capture information using fuzzy convolution neural networks","display_name":"Human action recognition based on motion capture information using fuzzy convolution neural networks","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2065502920","doi":"https://doi.org/10.1109/icapr.2015.7050706","mag":"2065502920"},"language":"en","primary_location":{"id":"doi:10.1109/icapr.2015.7050706","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icapr.2015.7050706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)","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/A5061023457","display_name":"Earnest Paul Ijjina","orcid":"https://orcid.org/0000-0003-1988-5139"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Earnest Paul Ijjina","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India","Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India 502205"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India 502205","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012566120","display_name":"C. Krishna Mohan","orcid":"https://orcid.org/0000-0002-7316-0836"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"C Krishna Mohan","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India","Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India 502205"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India","institution_ids":["https://openalex.org/I65181880"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Hyderabad, Telangana, India 502205","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I65181880"],"apc_list":null,"apc_paid":null,"fwci":1.622,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.91621279,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9968000054359436,"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":0.9950000047683716,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.773252010345459},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7301551103591919},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7267223000526428},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6888959407806396},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6608864068984985},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.624880313873291},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5926730632781982},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5591922402381897},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5033690333366394},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4906281530857086},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.47541457414627075},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4196823239326477},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3721016049385071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3249904215335846}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.773252010345459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7301551103591919},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7267223000526428},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6888959407806396},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6608864068984985},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.624880313873291},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5926730632781982},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5591922402381897},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5033690333366394},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4906281530857086},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.47541457414627075},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4196823239326477},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3721016049385071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3249904215335846},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icapr.2015.7050706","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icapr.2015.7050706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1923186697","https://openalex.org/W1963932623","https://openalex.org/W1983364832","https://openalex.org/W1989560997","https://openalex.org/W2000143015","https://openalex.org/W2012996999","https://openalex.org/W2034014085","https://openalex.org/W2058256495","https://openalex.org/W2072128103","https://openalex.org/W2086509056","https://openalex.org/W2125073690","https://openalex.org/W2137435234","https://openalex.org/W2145546283","https://openalex.org/W2151047074","https://openalex.org/W2187281534","https://openalex.org/W2655896018","https://openalex.org/W4231109964","https://openalex.org/W6640204118"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2964954556"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,19],"novel":[6],"approach":[7],"for":[8,63,84],"human":[9,29,104],"action":[10,60,85],"recognition":[11],"based":[12],"on":[13,116],"motion":[14],"capture":[15],"(MOCAP)":[16],"information":[17,27],"using":[18],"Fuzzy":[20,48],"convolutional":[21,88],"neural":[22,89],"network.":[23],"The":[24,66],"MOCAP":[25],"tracking":[26],"of":[28,38,45,69,93,123],"joints":[30,41],"is":[31,78,100],"used":[32],"to":[33,52,102],"compute":[34],"the":[35,43,54,81,107,111,121,124],"temporal":[36,67],"variation":[37,68],"displacement":[39],"between":[40],"during":[42],"execution":[44],"an":[46],"action.":[47],"membership":[49,70,76],"functions":[50,77],"designed":[51],"emphasize":[53],"discriminative":[55],"pose":[56],"associated":[57,72],"with":[58,73],"each":[59],"are":[61],"considered":[62,79],"feature":[64,82,112],"extraction.":[65],"values":[71],"these":[74],"fuzzy":[75],"as":[80],"representation":[83],"recognition.":[86],"A":[87],"network":[90],"(CNN)":[91],"capable":[92],"recognizing":[94],"local":[95,108],"patterns":[96,109],"in":[97,110],"input":[98],"data":[99],"trained":[101],"recognize":[103],"actions":[105],"from":[106],"representation.":[113],"Experimental":[114],"evaluation":[115],"Berkeley":[117],"MHAD":[118],"dataset":[119],"demonstrates":[120],"effectiveness":[122],"proposed":[125],"approach.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}