Sparsity in the eigenspace of signal covariance matrices is exploited in this paper for compression and denoising. Dimensionality reduction (DR) and quantization modules present i...
Recently, many global stereo methods have achieved good results by modeling a disparity surface as a Markov random field (MRF) and by solving an optimization problem with various ...
In this paper we develop a novel measure of information in a random variable based on its cumulative distribution that we dub cumulative residual entropy (CRE). This measure parall...
In this paper, we consider the problem of tracking nonrigid surfaces and propose a generic data-driven mesh deformation framework. In contrast to methods using strong prior models...
This paper presents a neural network approach to the problem of nding the dialogue act for a given utterance. So far only symbolic, decision tree and statistical approaches were ut...