Abstract
In this contribution we present an approach for 2D-3D pose estimation of 3D free-form surface models. In our scenario we observe a free-form object in an image of a calibrated camera. Pose estimation means to estimate the relative position and orientation of the 3D object to the reference camera system. The object itself is modeled as a two-parametric 3D surface and extended by one-parametric contour parts of the object. A twist representation, which is equivalent to a Fourier representation allows for a low-pass approximation of the object model, which is advantageously applied to regularize the pose problem. The experiments show, that our developed algorithms are fast (200ms/frame) and accurate (1o rotational error/frame).
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Rosenhahn, B., Sommer, G. (2004). Pose Estimation of Free-Form Objects. In: Pajdla, T., Matas, J. (eds) Computer Vision - ECCV 2004. ECCV 2004. Lecture Notes in Computer Science, vol 3021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24670-1_32
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DOI: https://doi.org/10.1007/978-3-540-24670-1_32
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