One challenge when tracking objects is to adapt the object representation depending on the scene context to account for changes in illumination, coloring, scaling, etc. Here, we p...
Ali Borji, Simone Frintrop, Dicky N. Sihite, Laure...
We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-squa...
The automatic generation of volumes bounding the intersection of two implicit surfaces (isosurfaces of real functions of 3D point coordinates) or Feature Based Volumes (FBV) is pr...
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
We propose an active vision system for object acquisition. The core of our approach is a reinforcement learning module which learns a strategy to scan an object. The agent moves a...
Gabriele Peters, Claus-Peter Alberts, Markus Bries...
We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
There are a lot of application domains, e.g. sensor databases, traffic management or recognition systems, where objects have to be compared based on vague and uncertain data. Feat...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
This paper presents an algorithm for constructing object representations suitable for recognition. The system automatically selects a representative subset of the views of the obj...
Jay Winkeler, B. S. Manjunath, Shivkumar Chandrase...