Motion Segmentation with Missing Data using PowerFactorization and GPCA
We consider the problem of segmenting multiple rigid motions from point correspondences in multiple affine views. We cast this problem as a subspace clustering problem in which the motion of each object lives in a subspace of dimension two, three or four. Unlike previous work, we do not restrict the motion subspaces to be four-dimensional or linearly independent. Instead, our approach deals gracefully with all the spectrum of possible affine motions: from two-dimensional and partially dependent...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition|
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