We propose a method that dramatically improves the performance of template-based matching in terms of size of convergence region and computation time. This is done by selecting a ...
Selim Benhimane, Alexander Ladikos, Vincent Lepeti...
Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...
We present a fast and accurate framework for registration of multi-modal volumetric images based on decoupled estimation of registration parameters utilizing spatial information i...
Parastoo Sadeghi, Ramtin Shams, Richard I. Hartley...
In this paper we propose a method for matching articulated shapes represented as large sets of 3D points by aligning the corresponding embedded clouds generated by locally linear ...
Diana Mateus, Fabio Cuzzolin, Radu Horaud, Edmond ...
We consider the problem of segmentation of images that can be modelled as piecewise continuous signals having unknown, non-stationary statistics. We propose a solution to this pro...