Literature DB >> 33604423

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

Cristina Nuzzi1, Simone Pasinetti1, Roberto Pagani1, Gabriele Coffetti1, Giovanna Sansoni1.   

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.
© 2021 The Authors.

Entities:  

Keywords:  Classification; Hand-Gesture Recognition; Human-Robot Interaction; Object Detector

Year:  2021        PMID: 33604423      PMCID: PMC7873347          DOI: 10.1016/j.dib.2021.106791

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


  1 in total

1.  HGM-4: A new multi-cameras dataset for hand gesture recognition.

Authors:  V T Hoang
Journal:  Data Brief       Date:  2020-05-08
  1 in total
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1.  Dataset for multi-channel surface electromyography (sEMG) signals of hand gestures.

Authors:  Mehmet Akif Ozdemir; Deniz Hande Kisa; Onan Guren; Aydin Akan
Journal:  Data Brief       Date:  2022-02-04
  1 in total

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