We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the obje...
"Pattern recognition techniques are concerned with the theory and algorithms of putting abstract objects, e.g., measurements made on physical objects, into categories. Typical...
In many applications, objects are represented by a collection of unorganized points that scan the surface of the object. In such cases, an efficient way of storing this information...
Computational biology research is now faced with the burgeoning number of genome data. The rigorous postprocessing of this data requires an increased role for high performance com...
In this paper, we explore the use of a Gaussian posteriorgram based representation for unsupervised discovery of speech patterns. Compared with our previous work, the new approach...