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GRIDDS - a gait recognition image and depth dataset

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Resumo:Several approaches based on human gait have been proposed in the literature, either for medical research reasons, smart surveillance, human-machine interaction, or other purposes, whose validation highly depends on the access to common input data through available datasets, enabling a coherent performance comparison. The advent of depth sensors leveraged the emergence of novel approaches and, consequently, the usage of new datasets. In this work we present the GRIDDS - A Gait Recognition Image and Depth Dataset, a new and publicly available gait depth-based dataset that can be used mostly for person and gender recognition purposes.
Autores principais:Nunes, João
Outros Autores:Moreira, Pedro Miguel; Tavares, João Manuel R. S.
Assunto:Gait Dataset Person Recognition Gender Recognition RGB-D Sensors GRIDDS
Ano:2019
País:Portugal
Tipo de documento:capítulo de livro
Tipo de acesso:acesso a metadados
Instituição associada:Instituto Politécnico de Viana do Castelo
Idioma:inglês
Origem:Repositório Científico IPVC

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