GRIDDS - A Gait Recognition Image and Depth Dataset

• Tipo: Capítulo ou Parte de Livro
• Data: 2019-10

Autores

João Ferreira Nunes (Autor) Outra; Pedro Miguel Moreira (Autor) Outra; João Manuel R. S. Tavares (Autor) FEUP

Livro

Título: VipIMAGE 2019 - Proceedings of the VII ECCOMAS Thematic = Lecture Notes in Computational Vision and Biomechanics

Páginas: 343-352

Editora: Springer

Indexação

ISI Proceedings

Scopus - 1 Citação

Classificação Científica

CORDIS: Ciências Tecnológicas

FOS: Ciências médicas e da saúde

Outras Informações

ID Authenticus: P-00R-5AE

DOI: 10.1007/978-3-030-32040-9_36

Abstract (EN): 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. © Springer Nature Switzerland AG 2019.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10