Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
This paper describes a local ensemble kernel learning technique to recognize/classify objects from a large number of diverse categories. Due to the possibly large intraclass featu...
In this paper we consider the problem of multi-object categorization. We present an algorithm that combines support vector machines with local features via a new class of Mercer k...
Barbara Caputo, Christian Wallraven, Maria-Elena N...
Abstract. The paper describes a fast system for appearance based image recognition . It uses local invariant descriptors and efficient nearest neighbor search. First, local affine ...