{"id":"https://openalex.org/W3163556836","doi":"https://doi.org/10.1109/icpr48806.2021.9412487","title":"Attention-Driven Body Pose Encoding for Human Activity Recognition","display_name":"Attention-Driven Body Pose Encoding for Human Activity Recognition","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3163556836","doi":"https://doi.org/10.1109/icpr48806.2021.9412487","mag":"3163556836"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5026549789","display_name":"Bappaditya Debnath","orcid":"https://orcid.org/0000-0002-2026-8632"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bappaditya Debnath","raw_affiliation_strings":["","Faculty of Arts & Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]},{"raw_affiliation_string":"Faculty of Arts & Sciences","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075851663","display_name":"Mary O'Brient","orcid":null},"institutions":[{"id":"https://openalex.org/I165525304","display_name":"Edge Hill University","ror":"https://ror.org/028ndzd53","country_code":"GB","type":"education","lineage":["https://openalex.org/I165525304"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mary O'Brient","raw_affiliation_strings":["Faculty of Health, Social Care & Medicine, Edge Hill University, Ormskirk, UK","Faculty of Health, Social Care & Medicine, Edge Hill University,Ormskirk,UK,L394QP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Health, Social Care & Medicine, Edge Hill University, Ormskirk, UK","institution_ids":["https://openalex.org/I165525304"]},{"raw_affiliation_string":"Faculty of Health, Social Care & Medicine, Edge Hill University,Ormskirk,UK,L394QP","institution_ids":["https://openalex.org/I165525304"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053838336","display_name":"Swagat Kumar","orcid":"https://orcid.org/0000-0001-7405-3445"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Swagat Kumar","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057980050","display_name":"Ardhendu Behera","orcid":"https://orcid.org/0000-0003-0276-9000"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ardhendu Behera","raw_affiliation_strings":[""],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9703,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.77147143,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5897","last_page":"5904"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9936000108718872,"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/computer-science","display_name":"Computer science","score":0.8390076160430908},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.7576635479927063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7409008741378784},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6447386145591736},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6062407493591309},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5597650408744812},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4842779040336609},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45301276445388794},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.444564551115036},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41983866691589355},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.4163975119590759}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8390076160430908},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.7576635479927063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7409008741378784},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6447386145591736},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6062407493591309},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5597650408744812},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4842779040336609},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45301276445388794},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.444564551115036},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41983866691589355},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.4163975119590759},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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":69,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W1441581489","https://openalex.org/W1514535095","https://openalex.org/W1522734439","https://openalex.org/W1923211482","https://openalex.org/W1950788856","https://openalex.org/W1969117674","https://openalex.org/W1983364832","https://openalex.org/W1983592444","https://openalex.org/W2048821851","https://openalex.org/W2058256495","https://openalex.org/W2078885226","https://openalex.org/W2097117768","https://openalex.org/W2133564696","https://openalex.org/W2143267104","https://openalex.org/W2151047074","https://openalex.org/W2160144863","https://openalex.org/W2162033023","https://openalex.org/W2166294429","https://openalex.org/W2192598490","https://openalex.org/W2194775991","https://openalex.org/W2217325140","https://openalex.org/W2245620145","https://openalex.org/W2269938945","https://openalex.org/W2295038166","https://openalex.org/W2309561466","https://openalex.org/W2471695703","https://openalex.org/W2510185399","https://openalex.org/W2550143307","https://openalex.org/W2556782416","https://openalex.org/W2593146028","https://openalex.org/W2604321021","https://openalex.org/W2607707631","https://openalex.org/W2613570903","https://openalex.org/W2752848408","https://openalex.org/W2783128845","https://openalex.org/W2798644314","https://openalex.org/W2799409595","https://openalex.org/W2804078698","https://openalex.org/W2894087839","https://openalex.org/W2950568498","https://openalex.org/W2952587893","https://openalex.org/W2963076818","https://openalex.org/W2963218601","https://openalex.org/W2963273301","https://openalex.org/W2963403868","https://openalex.org/W2963750390","https://openalex.org/W2964134613","https://openalex.org/W2964222622","https://openalex.org/W2964308564","https://openalex.org/W2964350391","https://openalex.org/W3098538019","https://openalex.org/W3099884890","https://openalex.org/W3101849660","https://openalex.org/W4294557331","https://openalex.org/W4385245566","https://openalex.org/W6618372016","https://openalex.org/W6628276711","https://openalex.org/W6630875275","https://openalex.org/W6640754710","https://openalex.org/W6684983439","https://openalex.org/W6698200468","https://openalex.org/W6704520437","https://openalex.org/W6725062358","https://openalex.org/W6730028046","https://openalex.org/W6736943367","https://openalex.org/W6739901393","https://openalex.org/W6747795875","https://openalex.org/W6754693662"],"related_works":["https://openalex.org/W3195649134","https://openalex.org/W4293226380","https://openalex.org/W2281498195","https://openalex.org/W4375867731","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"This":[0],"article":[1],"proposes":[2],"a":[3,64,73,92,121,140,152,168,177,181,203],"novel":[4,65,204],"attention-based":[5],"body":[6,51,78,88,102,118,131,198],"pose":[7,24,89,147,199],"encoding":[8],"for":[9,208],"human":[10,17,210],"activity":[11,18,211],"recognition.":[12,212],"Most":[13],"of":[14,76,116,129],"the":[15,28,49,84,97,113,126,134,159,163,189,196,222],"existing":[16],"recognition":[19],"approaches":[20],"based":[21],"on":[22,218],"3D":[23,50,77],"data":[25,30,47,54],"often":[26],"enrich":[27],"input":[29],"using":[31,167],"additional":[32],"handcrafted":[33],"representations":[34,71],"such":[35],"as":[36],"velocity,":[37],"super-normal":[38],"vectors,":[39],"pairwise":[40],"relations,":[41],"and":[42,55,180,226],"so":[43],"on.":[44],"The":[45,213],"enriched":[46],"complements":[48],"joint":[52],"position":[53],"improves":[56],"model":[57,174,207,215],"performance.":[58],"In":[59],"this":[60,82],"paper,":[61],"we":[62],"propose":[63],"approach":[66,85],"that":[67,124],"learns":[68,125],"enhanced":[69,142],"feature":[70],"from":[72,162],"given":[74],"sequence":[75,136],"joints.":[79],"To":[80],"achieve":[81],"encoding,":[83],"exploits":[86],"two":[87,146],"streams:":[90],"1)":[91],"spatial":[93,98,110,114],"stream":[94,123,166,192,200],"which":[95],"encodes":[96],"relationship":[99],"between":[100],"various":[101],"joints":[103,119,132],"at":[104],"each":[105],"time":[106],"point":[107],"to":[108,138,201],"learn":[109],"structure":[111],"involving":[112],"distribution":[115],"different":[117],"2)":[120],"temporal":[122,127],"variation":[128],"individual":[130],"over":[133],"entire":[135],"duration":[137],"present":[139],"temporally":[141],"representation.":[143],"Afterwards,":[144],"these":[145],"streams":[148],"are":[149],"fused":[150,197],"with":[151,176,195],"multi-head":[153,178],"attention":[154,179],"mechanism.":[155],"We":[156],"also":[157],"capture":[158],"contextual":[160],"information":[161],"RGB":[164,190],"video":[165,191],"deep":[169,206],"Convolutional":[170],"Neural":[171],"Network":[172],"(CNN)":[173],"combined":[175,194],"bidirectional":[182],"Long":[183],"Short-Term":[184],"Memory":[185],"(LSTM)":[186],"network.":[187],"Finally,":[188],"is":[193,216],"give":[202],"end-to-end":[205],"effective":[209],"proposed":[214],"evaluated":[217],"three":[219],"datasets":[220],"including":[221],"challenging":[223],"NTU-RGBD":[224],"dataset":[225],"achieves":[227],"state-of-the-art":[228],"results.":[229]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}