Abstract
We present a variational approach to the problem of registering planar shapes despite missing parts. Registration is achieved through the evolution of a partial differential equation that simultaneously estimates the shape of the missing region, the underlying “complete shape” and the collection of group elements (Euclidean or affine) corresponding to the registration. Our technique applies both to shapes, for instance represented as characteristic functions (binary images), and to grayscale images, where all intensity levels evolve simultaneously in a partial differential equation. It can therefore be used to perform “region inpainting” and to register collections of images despite occlusions. The novelty of the approach lies on the fact that, rather than estimating the missing region in each image independently, we pose the problem as a joint registration with respect to an underlying “complete shape” from which the complete version of the original data is obtained via a group action.
This research is sponsored in part by ARO grant DAAD19-99-1-0139 and Intel grant 8029.
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Duci, A., Yezzi, A.J., Mitter, S., Soatto, S. (2002). Region Matching with Missing Parts. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47977-5_4
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