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Combination of RGB-D Features for Head and Upper Body Orientation Classification

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10016))

Abstract

In Human-Robot Interaction (HRI), the intention of a person to interact with another agent (robot or human) can be inferred from his/her head and upper body orientation. Furthermore, additional information on the person’s overall intention and motion direction can be determined with the knowledge of both orientations. This work presents an exhaustive evaluation of various combinations of RGB and depth image features with different classifiers. These evaluations intend to highlight the best feature representation for the body part orientation to classify, i.e., the person’s head or upper body. Our experiments demonstrate that high classification performances can be achieved by combining only three families of RGB and depth features and using a multiclass SVM classifier.

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Notes

  1. 1.

    For extensive evaluation results, please refer to the supplemental material at http://homepages.laas.fr/aamekonn/acivs16/supplement.pdf.

  2. 2.

    For extensive evaluation results, please refer to the supplemental material at http://homepages.laas.fr/aamekonn/acivs16/supplement.pdf.

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Acknowledgment

This work is funded by the ROMEO2 project (http://www.projetromeo.com/) in the framework of the Structuring Projects of Competitiveness Clusters (PSPC).

Author information

Authors and Affiliations

  1. LAAS-CNRS, Université de Toulouse, CNRS, UPS, Toulouse, France

    Laurent Fitte-Duval, Alhayat Ali Mekonnen & Frédéric Lerasle

Authors
  1. Laurent Fitte-Duval
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  2. Alhayat Ali Mekonnen
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  3. Frédéric Lerasle
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Corresponding author

Correspondence to Alhayat Ali Mekonnen .

Editor information

Editors and Affiliations

  1. Université Paris-Sud 11 , Orsay, France

    Jacques Blanc-Talon

  2. University of Salento , Lecce, Lecce, Italy

    Cosimo Distante

  3. Ghent University , Gent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre , Sydney, New South Wales, Australia

    Dan Popescu

  5. University of Antwerp , Wilrijk, Belgium

    Paul Scheunders

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Fitte-Duval, L., Mekonnen, A.A., Lerasle, F. (2016). Combination of RGB-D Features for Head and Upper Body Orientation Classification. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_52

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  • DOI: https://doi.org/10.1007/978-3-319-48680-2_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48679-6

  • Online ISBN: 978-3-319-48680-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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