| Texto completo | |
| Autor(es): Mostrar menos - |
Goncalves Dos Santos, Claudio Filipi
;
Oliveira, Diego De Souza
;
Passos, Leandro A.
;
Pires, Rafael Goncalves
;
Silva Santos, Daniel Felipe
;
Valem, Lucas Pascotti
;
Moreira, Thierry P.
;
Santana, Marcos Cleison S.
;
Roder, Mateus
;
Papa, Joao Paulo
;
Colombo, Danilo
Número total de Autores: 11
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| Tipo de documento: | Artigo Científico |
| Fonte: | ACM COMPUTING SURVEYS; v. 55, n. 2, p. 34-pg., 2023-03-01. |
| Resumo | |
In general, biometry-based control systems may not rely on individual expected behavior or cooperation to operate appropriately. Instead, such systems should be aware of malicious procedures for unauthorized access attempts. Some works available in the literature suggest addressing the problem through gait recognition approaches. Such methods aim at identifying human beings through intrinsic perceptible features, despite dressed clothes or accessories. Although the issue denotes a relatively long-time challenge, most of the techniques developed to handle the problem present several drawbacks related to feature extraction and low classification rates, among other issues. However, deep learning-based approaches recently emerged as a robust set of tools to deal with virtually any image and computer-vision-related problem, providing paramount results for gait recognition as well. Therefore, this work provides a surveyed compilation of recent works regarding biometric detection through gait recognition with a focus on deep learning approaches, emphasizing their benefits and exposing their weaknesses. Besides, it also presents categorized and characterized descriptions of the datasets, approaches, and architectures employed to tackle associated constraints. (AU) | |
| Processo FAPESP: | 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo? |
| Beneficiário: | Alexandre Xavier Falcão |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 20/12101-0 - Suporte para o ambiente computacional e execução de experimentos: aquisição de dados, categorização e manutenção |
| Beneficiário: | Leandro Aparecido Passos Junior |
| Modalidade de apoio: | Bolsas no Brasil - Programa Capacitação - Treinamento Técnico |
| Processo FAPESP: | 19/07665-4 - Centro de Inteligência Artificial |
| Beneficiário: | Fabio Gagliardi Cozman |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa eScience e Data Science - Centros de Pesquisa em Engenharia |
| Processo FAPESP: | 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria |
| Beneficiário: | Francisco Louzada Neto |
| Modalidade de apoio: | Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs |