Activity modelling and unusual event detection in a network of cameras is challenging particularly when the camera views are not overlapped. We show that it is possible to detect u...
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Generative 3D Face Models are expressive models with applications in modelling and editing. They are learned from example faces, and offer a compact representation of the continuou...
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...