Upper-Body Pose Estimation Using Geodesic Distances and Skin-Color

  • Sebastian Handrich
  • Ayoub Al-Hamadi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)


We propose a real-time capable method for human pose estimation from depth and color images that does not need any pre-trained pose classifiers. The pose estimation focuses on the upper body, as it is the relevant part for a subsequent gesture and posture recognition and therefore the basis for a real human-machine-interaction. Using a graph-based representation of the 3D point cloud, we compute geodesic distances between body parts. The geodesic distances are independent of pose and allow the robust determination of anatomical landmarks which serve as input to a skeleton fitting process using inverse kinematics. In case of degenerated graphs, landmarks are tracked locally with a meanshift algorithm based on skin color probability.


Point Cloud Hand Position Depth Image Gesture Recognition Geodesic Distance 
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 2013

Authors and Affiliations

  • Sebastian Handrich
    • 1
  • Ayoub Al-Hamadi
    • 1
  1. 1.Institute of Information Technology and CommunicationsOtto-von-Guericke-University MagdeburgGermany

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