Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
In this paper we propose a novel prior-based variational object segmentation method in a global minimization framework which unifies image segmentation and image denoising. The id...
Anders Heyden, Christian Gosch, Christoph Schn&oum...
Enterprises today wish to manage their IT resources so as to optimize business objectives, such as income, rather than IT metrics, such as response times. Therefore, we introduce ...
This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object dete...
Jens Klappstein, Tobi Vaudrey, Clemens Rabe, Andre...
Our objective is transfer training of a discriminatively trained object category detector, in order to reduce the number of training images required. To this end we propose three ...