Multiview 3D Warps

Image registration and 3D reconstruction are fundamental computer vision and medical imaging problems. They are particularly challenging when the input data are images of a deforming body obtained by a single moving camera. We propose a new modelling framework, the multiview 3D warps. Existing models are twofold: they estimate interimage warps which are often inconsistent between the different images and do not model the underlying 3D structure, or reconstruct just a sparse set of points. In contrast, our multiview 3D warps combine the advantages of both; they have an explicit 3D component and a set of 3D deformations combined with projection to 2D. They thus capture the dense deforming body’s time-varying shape and camera pose. The advantages over the classical solutions are numerous: thanks to our feature-based estimation method for the multiview 3D warps, one can not only augment the original images but also retarget or clone the observed body’s 3D deformations by changing the ...

• Type: Journal
• Year: 2011
• Where: ICCV
• Authors: Alessio Del Bue, Adrien Bartoli
• Keywords: 3D Reconstruction, Computer Vision, Explicit 3d, ICCV 2011, Sparse Set