We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
We propose a new boosting algorithm for sequence classification, in particular one that enables early classification of multiple classes. In many practical problems, we would like...
In object recognition problems a two-stage system is usually adopted composed of a fast and simple detector and a more complex classifier. This paper studies a design of the secon...
In this paper we address the problem of classifying vector sets. We motivate and introduce a novel method based on comparisons between corresponding vector subspaces. In particula...
Tae-Kyun Kim, Ognjen Arandjelovic, Roberto Cipolla
This paper proposes a novel method for rapid and robust human detection and tracking based on the omega-shape features of people's head-shoulder parts. There are two modules ...