Hand gestures are one of the natural forms of communication in human-robot interaction scenarios. They can be used to delegate tasks from a human to a robot. To facilitate human-like interaction with robots, a major requirement for advancing in this direction is the availability of a hand gesture dataset for judging the performance of the proposed algorithms.

Dataset Features

• 22 participants performing 8 hand gestures in context of human-robot interaction scenarios taking place in close proximity.
• 8 hand gestures categorized as: (1) 2 types of referencing (pointing) gestures with the ground truth location of the target pointed at, (2) 2 symbolic gestures, (3) 2 manipulative gestures, (4) 2 interactional gestures.
• Hand gestures recorded from two views using RGB-D Kinect sensor.

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Reference

Dadhichi Shukla, Ozgur Erkent, Justus Piater, The IMHG dataset: A Multi-View Hand Gesture RGB-D Dataset for Human-Robot Interaction. Towards Standardized Experiments in Human Robot Interactions, 2015 (Workshop at IROS). Extended Abstract.PDF.

BibTex

  @InProceedings{Shukla-2015-StandardHRI,
    title = {{The IMHG dataset: A Multi-View Hand Gesture RGB-D Dataset for Human-Robot Interaction}},
    author = {Shukla, Dadhichi and Erkent, Ozgur and Piater, Justus},
    booktitle = {{Towards Standardized Experiments in Human Robot Interactions}},
    year = 2015,
    month = 10,
    note = {Workshop at IROS},
    url = {https://iis.uibk.ac.at/public/papers/Shukla-2015-StandardHRI.pdf}
  }

Acknowledgement

The research leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/2007-2013 (Specific Programme Cooperation, Theme 3, Information and Communication Technologies) under grant agreement no. 610878, 3rd HAND.

Contact

dadhichi[dot]shukla[at]uibk[dot]ac[dot]at