We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
Object tracking is one of the fundamental problems in computer vision and has received considerable attention in the past two decades. The success of a tracking algorithm relies on...
In Proc. European Conf. Computer Vision, 1996, pp. 357{368, Cambridge, UK The performance of Active Contours in tracking is highly dependent on the availability of an appropriate ...
David Reynard, Andrew Wildenberg, Andrew Blake, Jo...
Here we explore a discriminative learning method on underlying generative models for the purpose of discriminating between object categories. Visual recognition algorithms learn m...
We present a cognitive model that bridges work in analogy and category learning. The model, Building Relations through Instance Driven Gradient Error Shifting (BRIDGES), extends A...