Publicação
GRIDDS - a gait recognition image and depth dataset
| 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. |
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| 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 |
| 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. |
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