Choosing the appropriate type of video input is an important issue for any vision-based system and the right decision must take into account the specific requirements of the inten...
We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled f...
Learning models for recognizing objects with few or no training examples is important, due to the intrinsic longtailed distribution of objects in the real world. In this paper, we...
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
We propose a method that rates the suitability of given templates for template-based tracking in real-time. This is important for applications with online template selection, such...