Body-Part Templates for Recovery of 2D Human Poses under Occlusion

  • Ronald Poppe
  • Mannes Poel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5098)


Detection of humans and estimation of their 2D poses from a single image are challenging tasks. This is especially true when part of the observation is occluded. However, given a limited class of movements, poses can be recovered given the visible body-parts. To this end, we propose a novel template representation where the body is divided into five body-parts. Given a match, we not only estimate the joints in the body-part, but all joints in the body. Quantitative evaluation on a HumanEva walking sequence shows mean 2D errors of approximately 27.5 pixels. For simulated occlusion of the head and arms, similar results are obtained while occlusion of the legs increases this error by 6 pixels.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ronald Poppe
    • 1
  • Mannes Poel
    • 1
  1. 1.Human Media Interaction Group, Dept. of Computer ScienceUniversity of TwenteEnschedeThe Netherlands

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