We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
We propose a novel and robust model to represent and learn generic 3D object categories. We aim to solve the problem of true 3D object categorization for handling arbitrary rotati...
We present a new and computationally efficient scheme for classifying signals into a fixed number of known classes. We model classes as subspaces in which the corresponding data...
Procedural encoding of scattered and unstructured scalar datasets using Radial Basis Functions (RBF) is an active area of research with great potential for compactly representing ...
Manfred Weiler, Ralf P. Botchen, Simon Stegmaier, ...
We describe a novel method of evolutionary visual learning that uses generative approach for assessing learner’s ability to recognize image contents. Each learner, implemented as...
Wojciech Jaskowski, Krzysztof Krawiec, Bartosz Wie...