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RAVEL: an annotated corpus for training robots with audiovisual abilities

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Journal on Multimodal User Interfaces Aims and scope Submit manuscript

Abstract

We introduce Ravel (Robots with Audiovisual Abilities), a publicly available data set which covers examples of Human Robot Interaction (HRI) scenarios. These scenarios are recorded using the audio-visual robot head POPEYE, equipped with two cameras and four microphones, two of which being plugged into the ears of a dummy head. All the recordings were performed in a standard room with no special equipment, thus providing a challenging indoor scenario. This data set provides a basis to test and benchmark methods and algorithms for audio-visual scene analysis with the ultimate goal of enabling robots to interact with people in the most natural way. The data acquisition setup, sensor calibration, data annotation and data content are fully detailed. Moreover, three examples of using the recorded data are provided, illustrating its appropriateness for carrying out a large variety of HRI experiments. The Ravel data are publicly available at: http://ravel.humavips.eu/.

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Notes

  1. http://perception.inrialpes.fr/POP/.

  2. http://www.irisa.fr/vista/Equipe/People/Ivan.Laptev.html.

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Acknowledgments

This work was supported by the EU project HUMAVIPS FP7-ICT-2009-247525.

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Authors and Affiliations

  1. INRIA Grenoble Rhône-Alpes, 655, Avenue de l’Europe, 38330 , Montobonnot, France

    Xavier Alameda-Pineda, Jordi Sanchez-Riera, Jan Čech, Kaustubh Kulkarni, Antoine Deleforge & Radu Horaud

  2. Universität Bielefeld, Universitätsstraße 25, 33615 , Bielefeld, Germany

    Johannes Wienke

  3. Czech Technical University, Technická 2, 166 27 , Prague, Czech Republic

    Vojtěch Franc

Authors
  1. Xavier Alameda-Pineda
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  2. Jordi Sanchez-Riera
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  3. Johannes Wienke
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  4. Vojtěch Franc
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  5. Jan Čech
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  6. Kaustubh Kulkarni
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  7. Antoine Deleforge
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  8. Radu Horaud
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Correspondence to Xavier Alameda-Pineda.

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Alameda-Pineda, X., Sanchez-Riera, J., Wienke, J. et al. RAVEL: an annotated corpus for training robots with audiovisual abilities. J Multimodal User Interfaces 7, 79–91 (2013). https://doi.org/10.1007/s12193-012-0111-y

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  • DOI: https://doi.org/10.1007/s12193-012-0111-y

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