This paper presents a novel algorithm which generates three-dimensional face point trajectories for a given speech le with or without its text. The proposed algorithm rst employs an oo-line training phase. In this phase, recorded face point trajectories along with their speech data and phonetic labels are used to generate phonetic codebooks. These codebooks consist of both acoustic and visual f...

Full perspective mappings between D objects and D images are more complicated than weak perspective mappings which consider only rotation translation and scaling Therefore in D model based robot navigation it is important to understand how and when full perspective must be taken into account In this paper we use a probabilistic combinatorial op timization algorithm to search for an optimal matc...

This paper presents algorithms developed for pixel merging phase of object space parallel polygon rendering on hypercube connected multicomputers These algorithms reduce volume of communication in pixel merging phase by only exchanging local foremost pixels In order to avoid message fragmentation local foremost pixels should be stored in consecutive memory locations An algorithm called modi ed ...

Evolutionary algorithms EAs are stochas tic population based algorithms inspired by the natural processes of recombination mu tation and selection EAs are often em ployed as optimum seeking techniques A for mal framework for EAs is proposed in which evolutionary operators are viewed as map pings from parameter spaces to spaces of ran dom functions Formal de nitions within this framework capture...

We present a new algorithm for inferring the home locations of Twitter users at different granularities, such as city, state, or time zone, using the content of their tweets and their tweeting behavior. Unlike existing approaches, our algo rithm uses an ensemble of statistical and heuristic classifiers to predict locations. We find that a hierarchical classifica tion approach can improve predic...

In this paper a particle gradient evolutionary algorithm is presented for solving complex single-objective optimization problems based on statistical mechanics theory, the principle of gradient descending, and the law of evolving chance ascending of particles. Numerical experiments show that we can easily solve complex single-objective optimiz ation problems that are difficult to solve by using...

presented here is a generalization of the implicit enumeration algorithm that can be applied when the objec-tive function is being maximized and can be rewritten as the difference of two non-decreasing functions. also developed is a computational algorithm, named linear speedup, to use whatever explicit linear constraints are present to speedup the search for a solution. the method is easy to u...

In this paper we study geometrical structures on the manifold of FIR lters and their application to multichannel blind deconvolution First we introduce the Lie group and Riemannian metric to the manifold of FIR lters Then we derive the natu ral gradient on the manifold using the isometry of the Riemannian metric Using the natural gradient we present a novel learning algorithm for blind deconvol...

We propose a rigorous study of an ierative maximization algo rithm introduced by Geyer and Thompson for maximum likelihood estimation of Markov random elds One step of the algorithm consists in a Monte Carlo approximation of the likelihood followed by a local maximization in the neigh borhood of the current parameter We study convergence properties of the induced process and bound the computati...

Set constraints are inclusion relations between expressions denoting sets of ground terms over a ranked alphabet They are the main ingredient in set based program analysis In this paper we describe a constraint logic programming language clp sc over set constraints in the style of Ja ar and Lassez The language subsumes ordinary logic programs over an Herbrand domain We give an e cient uni catio...