In this paper we present an image-based algorithm to render visually plausible anti-aliased soft shadows in real time. Our technique employs a new shadow pre-filtering method based on an extended exponential shadow mapping theory. The algorithm achieves faithful contact shadows by adopting an optimal approximation to exponential shadow reconstruction function. Benefiting from a novel overflow f...

When using a gradient-based method to determine the optical flow field for an image sequence, it is generally appreciated that some spatial pre-filtering of the images is usually needed, particularly for large motion values. However the characteristics of the filter are not generally given. In this paper we analyse the motion measurement from the point of view of sampling theory. We show how an...

A discrete regularization framework on graphs is proposed and studied for color image filtering purposes when images are represented by grid graphs. Image filtering is considered as a variational problem which consists in minimizing an appropriate energy function. In this paper, we propose a general discrete regularization framework defined on weighted graphs which can be seen as a discrete ana...

In this paper, we present a modelling of tree filtering mechanisms in logical-based grammars. This filtering permits restriction of the excessive generative capacity of syntactic parsing grammars. In order to preserve the declarative aspect of natural language grammars, we consider syntactic parsing as a deduction process; tree filtering consists in the reduction of the allowed forms of the pro...

We study and develop a robust control framework for malware filtering and network security. We investigate the malware filtering problem by capturing the tradeoff between increased security on one hand and continued usability of the network on the other. We analyze the problem using a linear control system model with a quadratic cost structure and develop algorithms based on H∞-optimal control ...

The problem of filtering information from large correlation matrices is of great importance in many applications. We have recently proposed the use of the Kullback–Leibler distance to measure the performance of filtering algorithms in recovering the underlying correlation matrix when the variables are described by a multivariate Gaussian distribution. Here we use the Kullback–Leibler distance t...

The problem of building recommender systems has attracted considerable attention in recent years. Collaborative Filtering (CF) is one of the most successful and widely used approaches in recommend system. Traditional collaborative filtering requires explicit user participation for providing his/her interest to the items. In this paper, we propose a novel collaborative filtering approach based o...

Mutual information is calculated for processes described by stochastic differential equations. The expression for the mutual information has an interpretation in filtering theory.

Tyrone Duncan has made seminal contributions in the field of Filtering, Stochastic Control and the interface of probability theory and geometry. In his pioneering thesis, he presented a fundamental theory of nonlinear filtering and was instrumental in introducing the modern theory of martingales as developed by Doob, Meyer, Kunita-Watanabe and others in the study of nonlinear filtering. As he s...