Abstract
Articulated motions are partially dependent. Most of the existing segmentation methods, e.g. Costeira and Kanade[2], can not be applied to articulated motions.
We propose a novel algorithm for articulated motion segmentation called RANSAC with priors. It does not require prior knowledge of the number of articulated parts. It is both robust and efficient. Its robustness comes from its RANSAC nature. Its efficiency is due to the priors, which are derived from the spectral affinities between every pair of trajectories.
We test our algorithm with synthetic and real data. In some highly challenging case, where other motion segmentation algorithms may fail, our algorithm still achieves robust results.
Though our algorithm is inspired by articulated motions, it also applies to independent motions which can be regarded as a special case and treated uniformly.
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Yan, J., Pollefeys, M. (2007). Articulated Motion Segmentation Using RANSAC with Priors. In: Vidal, R., Heyden, A., Ma, Y. (eds) Dynamical Vision. WDV WDV 2006 2005. Lecture Notes in Computer Science, vol 4358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70932-9_6
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DOI: https://doi.org/10.1007/978-3-540-70932-9_6
Publisher Name: Springer, Berlin, Heidelberg
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