Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
We propose a methodology for improved segmentation of images in a Bayesian framework by fusion of color, texture and gradient information. The proposed algorithm is initialized by...
Efficient intra-node shared memory communication is important for High Performance Computing (HPC), especially with the emergence of multi-core architectures. As clusters continue ...
We propose efficient particle smoothing methods for generalized state-spaces models. Particle smoothing is an expensive O(N2 ) algorithm, where N is the number of particles. We ov...
Mike Klaas, Mark Briers, Nando de Freitas, Arnaud ...
Texture mapping has become indispensable in image synthesis as an inexpensive source of rich visual detail. Less obvious, but just as useful, is its ability to mask image errors d...
Bruce Walter, Sumanta N. Pattanaik, Donald P. Gree...