{"id":"https://openalex.org/W7215280581","doi":null,"title":"An\u00e1lises de comportamento usando Vis\u00e3o Computacional para detec\u00e7\u00e3o de riscos","display_name":"An\u00e1lises de comportamento usando Vis\u00e3o Computacional para detec\u00e7\u00e3o de riscos","publication_year":2022,"publication_date":"2022-02-17","ids":{"openalex":"https://openalex.org/W7215280581"},"language":"pt","primary_location":{"id":"pmh:oai:ojs.poli.br:article/2107","doi":null,"is_oa":true,"landing_page_url":"http://revistas.poli.br/index.php/anais/article/view/2107","pdf_url":null,"source":{"id":"https://openalex.org/S4306501701","display_name":"Anais da Mostra de Extens\u00e3o, Inova\u00e7\u00e3o e Pesquisa","issn_l":"2359-2249","issn":["2359-2249"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2359-2249","raw_type":"info:eu-repo/semantics/article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"http://revistas.poli.br/index.php/anais/article/view/2107","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019696531","display_name":"Let\u00edcia Portela","orcid":"https://orcid.org/0000-0001-7214-1644","observed_orcids":["https://orcid.org/0000-0001-7214-1644"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Portela, Let\u00edcia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5118584735","display_name":"Bruno Jos\u00e9 Torres Fernandes","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jos\u00e9 Torres Fernandes, Bruno","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9922000169754028,"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":0.9922000169754028,"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":0.006200000178068876,"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":9.999999747378752e-05,"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/fall-detection","display_name":"fall detection","score":0.7329999804496765},{"id":"https://openalex.org/keywords/drowning-detection","display_name":"drowning detection","score":0.9959999918937683},{"id":"https://openalex.org/keywords/spatiotemporal-graph-convolutional-network","display_name":"spatio-temporal graph convolutional network","score":0.8190000057220459},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"singular value decomposition","score":0.8849999904632568},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"anomaly detection","score":0.8949999809265137},{"id":"https://openalex.org/keywords/video-classification","display_name":"video classification","score":0.4690000116825104},{"id":"https://openalex.org/keywords/emergency-response","display_name":"emergency response","score":0.40299999713897705},{"id":"https://openalex.org/keywords/human-behavior-analysis","display_name":"human behavior analysis","score":0.4959999918937683}],"concepts":[{"id":"https://openalex.org/C15708023","wikidata":"https://www.wikidata.org/wiki/Q80083","display_name":"Humanities","level":1,"score":0.47360000014305115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4230000078678131},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.41370001435279846},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27070000767707825},{"id":"https://openalex.org/C95318506","wikidata":"https://www.wikidata.org/wiki/Q6588467","display_name":"Textual entailment","level":3,"score":0.2524000108242035},{"id":"https://openalex.org/C195579931","wikidata":"https://www.wikidata.org/wiki/Q3623548","display_name":"Applied probability","level":2,"score":0.2386000007390976},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.22339999675750732},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21209999918937683},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2062000036239624}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:ojs.poli.br:article/2107","doi":null,"is_oa":true,"landing_page_url":"http://revistas.poli.br/index.php/anais/article/view/2107","pdf_url":null,"source":{"id":"https://openalex.org/S4306501701","display_name":"Anais da Mostra de Extens\u00e3o, Inova\u00e7\u00e3o e Pesquisa","issn_l":"2359-2249","issn":["2359-2249"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2359-2249","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:ojs.poli.br:article/2107","doi":null,"is_oa":true,"landing_page_url":"http://revistas.poli.br/index.php/anais/article/view/2107","pdf_url":null,"source":{"id":"https://openalex.org/S4306501701","display_name":"Anais da Mostra de Extens\u00e3o, Inova\u00e7\u00e3o e Pesquisa","issn_l":"2359-2249","issn":["2359-2249"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2359-2249","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"score":0.9763000011444092,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7215239321","https://openalex.org/W7033719415","https://openalex.org/W6986590780","https://openalex.org/W2547426677","https://openalex.org/W2715748306","https://openalex.org/W3043461977","https://openalex.org/W7212350992","https://openalex.org/W4415340663","https://openalex.org/W4411704878","https://openalex.org/W6968954179"],"abstract_inverted_index":{"A":[0,61,285,335],"identifica\u00e7\u00e3o":[1,322],"de":[2,13,47,64,71,86,94,107,112,123,152,154,165,167,186,207,219,226,228,236,238,242,252,261,263,268,278,292,295,299,304,323,329,333,346,366,373,383,392,404,411,416,418,420,424],"riscos":[3,35,131,243],"\u00e0":[4,132,244],"sa\u00fade":[5,133,384],"humana":[6],"com":[7,203,223,301],"Vis\u00e3o":[8,124,412],"Computacional":[9,125,413],"\u00e9":[10,248,270,344],"uma":[11,74,141,160,224,230],"\u00e1rea":[12],"pesquisa":[14,417],"que":[15,82,172,232,241,281,341,359,407],"est\u00e1":[16],"crescendo":[17],"em":[18,22,179,290,353,381],"relev\u00e2ncia,":[19],"como":[20,39,97,130],"visto":[21],"Angela":[23],"et":[24,29,49,53,58,101,199,209],"al.":[25,30,50,54,102,200,210],"(2012)":[26],"e":[27,42,56,73,88,255,294,308,318,368,396,422],"Waqas":[28],"(2018).":[31],"H\u00e1":[32],"diversos":[33],"poss\u00edveis":[34],"a":[36,69,189,204,276,394,409],"serem":[37],"detectados,":[38],"quedas,":[40,300],"afogamentos":[41],"convuls\u00f5es,":[43],"explorados":[44],"nos":[45],"trabalhos":[46],"Yves":[48],"(2017),":[51],"Anthony":[52],"(2021)":[55],"David":[57],"al.,":[59],"respectivamente.":[60],"detec\u00e7\u00e3o":[62,227,365],"automatizada":[63],"tais":[65],"situa\u00e7\u00f5es":[66,253,262,372],"pode":[67],"permitir":[68],"redu\u00e7\u00e3o":[70],"custos":[72],"maior":[75,234,257],"efici\u00eancia":[76],"no":[77,406],"reconhecimento":[78,153,291,298],"do":[79],"risco,":[80],"possibilitando":[81],"sejam":[83],"acionados":[84],"servi\u00e7os":[85],"emerg\u00eancia":[87],"evitando":[89],"complica\u00e7\u00f5es":[90,113],"maiores":[91],"por":[92,99,197],"demora":[93],"atendimento.":[95],"Afinal,":[96],"evidenciado":[98],"Peter":[100],"(2005),":[103],"um":[104,121,279],"menor":[105],"tempo":[106,391],"resposta":[108,393],"diminui":[109],"o":[110,118,126,148,177,266,342,360,390,400],"risco":[111],"dos":[114],"pacientes.":[115],"Dessa":[116,375],"forma,":[117,376],"projeto":[119,401],"prop\u00f5e":[120],"modelo":[122,182,343,361],"qual":[127],"classifica":[128],"v\u00eddeos":[129,171,187,237],"ou":[134,385],"atividades":[135,239],"normais.":[136],"Para":[137],"mont\u00e1-lo,":[138],"foi":[139,158,288,325],"feita":[140,159],"revis\u00e3o":[142,161],"sistem\u00e1tica":[143,162],"da":[144,150,163],"literatura,":[145],"objetivando":[146],"identificar":[147,347,354],"estado":[149],"arte":[151],"a\u00e7\u00f5es.":[155],"Al\u00e9m":[156],"disso,":[157],"literatura":[164],"bases":[166,303],"dados,":[168],"para":[169,176,272,364,370,388],"selecionar":[170],"contenham":[173],"a\u00e7\u00f5es":[174],"relevantes":[175],"problema":[178],"quest\u00e3o.":[180],"O":[181,246],"proposto":[183],"extra\u00ed":[184],"caracter\u00edsticas":[185,213],"utilizando":[188,217],"Spatial":[190],"Temporal":[191],"Graph":[192],"Convolutional":[193],"Network":[194],"(ST-GCN),":[195],"criada":[196],"Sijie":[198],"(2018),":[201],"pr\u00e9-treinada":[202],"base":[205,328],"Kinetics,":[206],"Jo\u00e3o":[208],"(2017).":[211],"Essas":[212],"s\u00e3o":[214],"ent\u00e3o":[215],"classificadas":[216],"Decomposi\u00e7\u00e3o":[218],"Valor":[220],"Singular":[221],"(SVD),":[222],"abordagem":[225,286],"anomalias,":[229],"vez":[231],"h\u00e1":[233],"volume":[235],"normais":[240],"sa\u00fade.":[245],"SVD":[247],"treinado":[249],"na":[250,259,321,327],"reconstru\u00e7\u00e3o":[251,260,269],"normais,":[254],"apresenta":[256],"erro":[258,267],"risco.":[264,374],"Portanto,":[265],"utilizado":[271,380],"classificar":[273],"os":[274,283],"v\u00eddeos,":[275],"partir":[277,336],"limiar":[280],"melhor":[282],"separe.":[284],"proposta":[287],"testada":[289],"quedas":[293,348],"afogamentos.":[296,355],"Em":[297],"as":[302],"dados":[305,330],"UR-Fall,":[306],"Up-Fall":[307],"Precis":[309],"Har,":[310],"foram":[311],"obtidas":[312],"acur\u00e1cias":[313],"de,":[314],"respectivamente,":[315],"100%,":[316],"98,62%":[317],"94,94%.":[319],"J\u00e1":[320],"afogamento,":[324,367],"obtida,":[326],"LifeGuard.IO,":[331],"38%":[332],"acur\u00e1cia.":[334],"desses":[337],"resultados":[338],"pode-se":[339],"concluir":[340],"capaz":[345],"corretamente,":[349],"por\u00e9m":[350],"encontra":[351],"dificuldades":[352],"Logo,":[356],"futuramente":[357],"espera-se":[358],"seja":[362],"aprimorado":[363],"ampliado":[369],"outras":[371],"ele":[377],"poder\u00e1":[378],"ser":[379],"ambientes":[382],"mesmo":[386],"resid\u00eancias":[387],"melhorar":[389],"acidentes":[395],"diminuir":[397],"custos.":[398],"Ademais,":[399],"agrega":[402],"conhecimento":[403],"ponta":[405],"tange":[408],"aplica\u00e7\u00f5es":[410],"ao":[414],"grupo":[415],"Reconhecimento":[419],"Padr\u00f5es":[421],"Processamento":[423],"Imagens.":[425]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-02T00:00:00"}
