Estimation of Human Orientation in Images Captured with a Range Camera

  • Sébastien Piérard
  • Damien Leroy
  • Jean-Frédéric Hansen
  • Marc Van Droogenbroeck
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6915)


Estimating the orientation of the observed person is a crucial task for some application fields like home entertainment, man-machine interaction, or intelligent vehicles. In this paper, we discuss the usefulness of conventional cameras for estimating the orientation, present some limitations, and show that 3D information improves the estimation performance.

Technically, the orientation estimation is solved in the terms of a regression problem and supervised learning. This approach, combined to a slicing method of the 3D volume, provides mean errors as low as 9.2°or 4.3°depending on the set of considered poses. These results are consistent with those reported in the literature. However, our technique is faster and easier to implement than existing ones.


Shape Descriptor Intrinsic Limitation Color Camera Orientation Estimation Intelligent Vehicle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sébastien Piérard
    • 1
  • Damien Leroy
    • 1
  • Jean-Frédéric Hansen
    • 1
  • Marc Van Droogenbroeck
    • 1
  1. 1.INTELSIG Laboratory, Montefiore InstituteUniversity of LiègeBelgium

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