Yu, Z., Khan, M. Z., Taha, A. , Imran, M. and Abbasi, Q. (2022) NodeNS Human Activity Dataset. [Data Collection]
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Collection description
To date, numerous types of collection devices have been used in the recognition of human activities. However, due to the scarcity of training data, the task of 3D point cloud labelling has not yet made significant progress. To overcome this challenge, it is aimed to deduce this data requirements gap, allowing deep learning methods to reach their full potential in 3D point cloud tasks. The dataset used for this process is comprised of dense point clouds acquired with the static ground sensor by the NodeNs company supported MIMO radar (NodeNs ZERO 60 GHz IQ radar). It contains multiple types of human being data ranging from one to four individuals and encompasses a range of human action scenarios, including standing, sitting, picking up, falling, and walking.
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| College / School: | College of Science and Engineering > School of Engineering |
| Date Deposited: | 26 Oct 2022 10:59 |
| URI: | https://researchdata.gla.ac.uk/id/eprint/1354 |
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