| Autor: |
Cristina Nuzzi, Simone Pasinetti, Roberto Pagani, Gabriele Coffetti, Giovanna Sansoni |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Data in Brief, Vol 35, Iss , Pp 106791- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2352-3409 |
| DOI: |
10.1016/j.dib.2021.106791 |
| Popis: |
The HANDS dataset has been created for human-robot interaction research, and it is composed of spatially and temporally aligned RGB and Depth frames. It contains 12 static single-hand gestures performed with both the right-hand and the left-hand, and 3 static two-hands gestures for a total of 29 unique classes. Five actors (two females and three males) have been acquired performing the gestures, each of them adopting a different background and light conditions. For each actor, 150 RGB frames and their corresponding 150 Depth frames per gesture have been collected, for a total of 2400 RGB frames and 2400 Depth frames per actor.Data has been collected using a Kinect v2 camera intrinsically calibrated to spatially align RGB data to Depth data. The temporal alignment has been performed offline using MATLAB, aligning frames with a maximum temporal distance of 66 ms.This dataset has been used in [1] and it is freely available at http://dx.doi.org/10.17632/ndrczc35bt.1. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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