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HANDS: an RGB-D dataset of static hand-gestures for human-robot interaction

Authors :
Cristina Nuzzi
Simone Pasinetti
Roberto Pagani
Gabriele Coffetti
Giovanna Sansoni
Source :
Data in Brief, Vol 35, Iss , Pp 106791- (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

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.

Details

Language :
English
ISSN :
23523409
Volume :
35
Issue :
106791-
Database :
Directory of Open Access Journals
Journal :
Data in Brief
Publication Type :
Academic Journal
Accession number :
edsdoj.52e628646129432982af171a96832cbd
Document Type :
article
Full Text :
https://doi.org/10.1016/j.dib.2021.106791