Abstract
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.
This work has been funded in part by the Swiss National Science Foundation and in part by the VISIONTRAIN RTN-CT-2004-005439 Marie Curie Action within the EC’s Sixth Framework Programme. The text reflects only the authors’ views and the Community is not liable for any use that may be made of the information contained therein.
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Fossati, A., Fua, P. (2008). Linking Pose and Motion. In: Forsyth, D., Torr, P., Zisserman, A. (eds) Computer Vision – ECCV 2008. ECCV 2008. Lecture Notes in Computer Science, vol 5305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88693-8_15
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DOI: https://doi.org/10.1007/978-3-540-88693-8_15
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