Efficient articulated trajectory reconstruction using dynamic programming and filters
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Simultaneous compaction and factorization of sparse image motion matrices
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
A unified view on deformable shape factorizations
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Learning spatially-smooth mappings in non-rigid structure from motion
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Application of heterogenous motion models towards structure recovery from motion
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Recursive non-rigid structure from motion with online learned shape prior
Computer Vision and Image Understanding
A Simple Prior-Free Method for Non-rigid Structure-from-Motion Factorization
International Journal of Computer Vision
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Non-rigid structure from motion (NR-SFM) is a difficult, underconstrained problem in computer vision. This paper proposes a new algorithm that revises the standard matrix factorization approach in NR-SFM. We consider two alternative representations for the linear space spanned by a small number K of 3D basis shapes. As compared to the standard approach using general rank-3K matrix factors, we show that improved results are obtained by explicitly modeling K complementary spaces of rank-3. Our new method is positively compared to the state-of-the-art in NR-SFM, providing improved results on high-frequency deformations of both articulated and simpler deformable shapes. We also present an approach for NR-SFM with occlusion.