We investigate a prototypical agent-based model, the Naming Game, on random geometric networks. The Naming Game is a minimal model, employing local communications that captures th...
Local features have proven very useful for recognition.
Manifold learning has proven to be a very powerful tool in
data analysis. However, manifold learning application for
imag...
Abstract—We are interested in topological analysis and processing of the large-scale distributed data generated by sensor networks. Naturally a large-scale sensor network is depl...
In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework tha...
Existing autocalibration techniques use numerical optimization algorithms that are prone to the problem of local minima. To address this problem, we have developed a method where ...