Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
In this paper, we develop methods to rapidly remove rough features from irregularly triangulated data intended to portray a smooth surface. The main task is to remove undesirable ...
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
In this paper, we apply an evolutionary algorithm to learning behavior on a novel, interesting task to explore the general issue of learning e ective behaviors in a complex enviro...