In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
We propose a new algorithm to solve sparse linear systems of equations over the integers. This algorithm is based on a p-adic lifting technique combined with the use of block matr...
Wayne Eberly, Mark Giesbrecht, Pascal Giorgi, Arne...
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Abstract. A datatype with increasing importance in GIS is what we call the location history–a record of an entity’s location in geographical space over an interval of time. Thi...
We analyze the amount of information needed to carry out model-based recognition tasks, in the context of a probabilistic data collection model, and independently of the recogniti...