Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Abstract. We present a novel method for dimensionality reduction and recognition based on Linear Discriminant Analysis (LDA), which specifically deals with the Small Sample Size (S...
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
We consider the problem of speeding up Entity Recognition systems that exploit existing large databases of structured entities to improve extraction accuracy. These systems requir...
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...