In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
The goal of this work is to find a fast method for motion estimation and motion segmentation. We chose to decompose the motion on a basis functions. That allows us to compute the ...
In this paper, we address the problem of color image restoration. Here, we model the image as a Markov Random Field (MRF) and propose a restoration algorithm in a multiresolution ...
P. K. Nanda, K. Sunil Kumar, S. Ghokale, Uday B. D...
In many real applications traditional superresolution methods fail to provide high-resolution images due to objectionable blur and inaccurate registration of input low-resolution ...
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...