In this paper we derive a sampling theorem, which is the first one to guarantee topology preservation during digitization of 3D objects. This new theorem is applicable to several ...
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...
We describe a novel technique for identifying semantically equivalent parts in images belonging to the same object class, (e.g. eyes, license plates, aircraft wings etc.). The vis...
The paper describes a method for automatically extracting informative feature hierarchies for object classification, and shows the advantage of the features constructed hierarchic...
In this paper we show that efficient object recognition can be obtained by combining informative features with linear classification. The results demonstrate the superiority of in...