In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...
We present a robust method for 3D reconstruction of closed surfaces from sparsely sampled parallel contours. A solution to this problem is especially important for medical segment...
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
—Many vision-based navigation systems are restricted to the use of only a limited number of landmarks when computing the camera pose. This limitation is due to the overhead of de...
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...