Conventional subspace learning or recent feature extraction methods consider globality as the key criterion to design discriminative algorithms for image classification. We demonst...
Yun Fu, Zhu Li, Junsong Yuan, Ying Wu, Thomas S. H...
In this paper we present a methodical evaluation of the performance of a new and two traditional approaches to automatic target recognition (ATR) based on silhouette representatio...
Visual tracking is one of the central problems in computer vision. A crucial problem of tracking is how to represent the object. Traditional appearance-based trackers are using inc...
We describe a novel and robust feature descriptor called ordinal spatial intensity distribution (OSID) which is invariant to any monotonically increasing brightness changes. Many t...
We develop an object classification method that can learn a novel class from a single training example. In this method, experience with already learned classes is used to facilita...