In this paper, we propose a novel variational framework for the reconstruction of dynamic objects from sparse and noisy tomographic data. Using an object-based scene model, we dev...
In this paper we develop a confidence measure that can determine if a given set of samples is suitable for inclusion in the reconstruction of a higher resolution dataset. The con...
This paper addresses the problem of the interpolation of 2-d spherical signals from non-uniformly sampled and noisy data. We propose a graph-based regularization algorithm to impr...
The method of Moving Least Squares (MLS) is a popular framework for reconstructing continuous functions from scattered data due to its rich mathematical properties and well-underst...
Christian Ledergerber, Gaël Guennebaud, Miriah ...
The Opie Project aims to develop a compiler to transform C codes written for row-major matrix representation into equivalent codes for Morton-order matrix representation, and to a...