In this paper we present a novel scale invariant interest point detector of blobs which incorporates the idea of blob movement along the scales. This trajectory of the blobs throug...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
In this paper we address two closely related problems. The first is the object detection problem, i.e., the automatic decision of whether a given image represents a known object o...
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
We present a new active active recognition scheme (using an uncalibrated camera) based on a new idea, appearancebased aspect graphs. The scheme is robust to background clutter, an...