Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
This paper deals with the problem of incorporating natural regularity conditions on the motion in an MAP estimator for structure and motion recovery from uncalibrated image sequen...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
Abstract. We describe a system for autonomous learning of visual object representations and their grasp affordances on a robot-vision system. It segments objects by grasping and mo...
Dirk Kraft, Renaud Detry, Nicolas Pugeault, Emre B...
A new algorithm and systematic evaluation is presented for searching a database via relevance feedback. It represents a new image display strategy for the PicHunter system [2, 1]....
Ingemar J. Cox, Matthew L. Miller, Thomas P. Minka...