Linking Pose and Motion

  • Andrea Fossati
  • Pascal Fua
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5305)


Algorithms designed to estimate 3D pose in video sequences enforce temporal consistency but typically overlook an important source of information: The 3D pose of an object, be it rigid or articulated, has a direct influence on its direction of travel.

In this paper, we use the cases of an airplane performing aerobatic maneuvers and of pedestrians walking and turning to demonstrate that this information can and should be used to increase the accuracy and reliability of pose estimation algorithms.


Video Sequence Ground Plane Color Histogram Angle Error Temporal Consistency 
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.

Supplementary material

978-3-540-88693-8_15_MOESM1_ESM.avi (3.3 mb)
Supplementary material(3,348 KB)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Andrea Fossati
    • 1
  • Pascal Fua
    • 1
  1. 1.Computer Vision Laboratory, École Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland

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