Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11960/3098
Title: | Benchmark RGB-D gait datasets : a systematic review |
Authors: | Nunes, João Moreira, Pedro Miguel Tavares, João Manuel R. S. |
Keywords: | Gait Datasets Depth Sensors Systematic Review |
Issue Date: | 2019 |
Citation: | Nunes, J. F., Moreira, P. M., & Tavares, J. M. R. S. (2019). Benchmark RGB-D gait datasets : a systematic review. 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. 366-372). Springer. https://doi.org/10.1007/978-3-030-32040-9_38 |
Abstract: | Human motion analysis has proven to be a great source of information for a wide range of applications. Several approaches for a detailed and accurate motion analysis have been proposed in the literature, as well as an almost proportional number of dedicated datasets. The relatively recent arrival of depth sensors contributed to an increasing interest in this research area and also to the emergence of a new type of motion datasets. This work focuses on a systematic review of publicly available depth-based datasets, encompassing human gait data which is used for person recognition and/or classification purposes. We have conducted this systematic review using the Scopus database. The herein presented survey, which to the best of our knowledge is the first one dedicated to this type of datasets, is intended to inform and aid researchers on the selection of the most suitable datasets to develop, test and compare their algorithms. |
URI: | http://hdl.handle.net/20.500.11960/3098 |
ISSN: | 2212-9413 2212-9391 |
Appears in Collections: | ESTG - Artigos indexados à WoS/Scopus |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
370706.pdf Restricted Access | 212.87 kB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.