In this paper, we propose a novel learning-based method for image hallucination, with image super-resolution being a specific application that we focus on here. Given a low-resolu...
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
In this paper, we propose a probabilistic videobased facial expression recognition method on manifolds. The concept of the manifold of facial expression is based on the observatio...