The problem of jointly detecting multiple objects and estimating their states from image observations is formulated in a Bayesian framework by modeling the collection of states as ...
Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Sute...
Searching for similar objects in metric-space databases can be efficiently solved by using index data structures. A number of alternative sequential indexes have been proposed in...
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
We propose a novel approach to image segmentation, called feature and spatial domain clustering. The method is devised to group pixel data by taking into account simultaneously bo...
—We describe and evaluate a suite of distributed and computationally efficient algorithms for solving a class of convex optimization problems in wireless sensor networks. The pr...