We present a method for automatically learning discriminative image patches for the recognition of given object classes. The approach applies discriminative training of log-linear...
In this paper we extend a method that uses image patch histograms and discriminative training to recognize objects in cluttered scenes. The method generalizes and performs well for...
Abstract. In recent years the problem of object recognition has received considerable attention from both the machine learning and computer vision communities. The key challenge of...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Parts-based recognition has been suggested for generalizing from few training views in categorization scenarios. In this paper we present the results of a comparative investigation...