We present a new Gaussian Process inference algorithm, called Online Sparse Matrix Gaussian Processes (OSMGP), and demonstrate its merits with a few vision applications. The OSMGP ...
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
Image segmentation with shape priors has received a lot of attention over the past years. Most existing work focuses on a linearized shape space with small deformation modes aroun...
Digital images have been used in growing number of applications from law enforcement and surveillance, to medical diagnosis and consumer photography. With such widespread populari...
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...