We develop new techniques for time series classification based on hierarchical Bayesian generative models (called mixed-effect models) and the Fisher kernel derived from them. A k...
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
In this paper, a novel multi-cue collaborative kernel tracking algorithm is proposed. A new constraint based on the property of cross ratio invariant enables tracking of objects i...
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
Our objective is to obtain a state-of-the art object category
detector by employing a state-of-the-art image classifier
to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...