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http://hdl.handle.net/20.500.11960/3099
Title: | GRIDDS - a gait recognition image and depth dataset |
Authors: | Nunes, João Moreira, Pedro Miguel Tavares, João Manuel R. S. |
Keywords: | Gait Dataset Person Recognition Gender Recognition RGB-D Sensors GRIDDS |
Issue Date: | 2019 |
Citation: | Nunes, J. F., Moreira, P. M., & Tavares, J. M. R. S. (2019). GRIDDS - a gait recognition image and depth dataset. In J. M. R. S. Tavares, & R. M. N Jorge (Eds.), VipIMAGE 2019 Proceedings of the VII ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing, October 16-18, 2019, Porto, Portugal, (pp. 343-352). https://doi.org/10.1007/978-3-030-32040-9_36 |
Abstract: | 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. |
URI: | http://hdl.handle.net/20.500.11960/3099 |
ISBN: | 978-3-030-32039-3 978-3-030-32040-9 |
ISSN: | 2212-9413 2212-9391 |
Appears in Collections: | ESTG - Artigos indexados à WoS/Scopus |
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