A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
ARIADNE is a European foundation that aims to foster "Share and Reuse" of learning resources. To support this goal, ARIADNE has created an infrastructure for managing lea...
This paper studies a method for learning a discriminative visual codebook for various computer vision tasks such as image categorization and object recognition. The performance of...
In this paper, we address the problem of learning an
adaptive appearance model for object tracking. In particular,
a class of tracking techniques called “tracking by detectionâ...