In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...
Abstract. In this paper, we present a new, biologically inspired perceptual feature to solve the selectivity and invariance issue in object recognition. Based on the recent findin...
Abstract. Domain adaptation is an important emerging topic in computer vision. In this paper, we present one of the first studies of domain shift in the context of object recogniti...
Kate Saenko, Brian Kulis, Mario Fritz, Trevor Darr...
Abstract. Most current approaches to recognition aim to be scaleinvariant. However, the cues available for recognizing a 300 pixel tall object are qualitatively different from tho...
This paper compares two methods for object localization from contours: shape context and chamfer matching of templates. In the light of our experiments, we suggest improvements to...
Arasanathan Thayananthan, Bjoern Stenger, Philip H...